Celesta Capital is a venture capital firm that invests in entrepreneurs and disruptive technology companies. Their management team and investment professionals leverage over 400 years of accumulated investment and operational experience and bring to their portfolio companies a deep and unmatched network of value-added strategic relationships.  Celesta Capital invests globally and has offices in California, Israel, India, and China

Celesta Capital

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

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

Atlantic Bridge is a Growth Equity Firm with a Cross Border Value Add strategy. We invest in deep technology companies in Europe and the US. Our team is made up of successful entrepreneurs and senior technology industry executives and we invest in strong ambitious entrepreneurs and management teams that have the passion and drive to scale up and exploit major growth opportunities. We help our portfolio companies expand and grow internationally through our global platform with our team and offices in London, Dublin, Munich, Paris and Palo Alto. Atlantic Bridge brings together a unique team of technology entrepreneurs, experienced managers, finance professionals, and investment experts. The team contains a wealth of international business experience across Europe, the UK and the US. They have worked together in various capacities for the last 30 years, bringing a true partnership approach to their firm and their investments. Its investors include the founders, leading institutional investors, and private investors with a track record of investment in successful technology companies. Atlantic Bridge has developed a unique and differentiated strategy that focuses on specific technology themes and the implementation of the “Atlantic Bridge Model” for scaling companies internationally. The “Bridge Model” accelerates the scale-up of technology companies in Europe and the US. This approach is highly differentiated and has delivered strong performance results to date.

Atlantic Bridge

Redline Capital Management S.A. (RCM) manages a Luxembourg based and regulated fund, investing in Technology companies across North America, Europe, and Israel.

Redline Capital

Intel Capital invests in innovative startups targeting cloud and AI infrastructure, edge, 5G, autonomy, cybersecurity, client & gaming, enterprise applications, silicon design and manufacturing, and a wide range of other disruptive technologies.

Intel Capital

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

SoftBank Vision Fund is a subsidiary of Softbank Group that specializes in growth capital and social impact investments. Sectors that the fund invests in include the internet of things, artificial intelligence (AI), robotics, communications infrastructure, telecoms, computational biology, biotech, cloud technologies and software, consumer internet businesses, financial technology, and mobile apps. The Fund is designed to be a catalyst for technology progress in anticipation that it will expand SoftBank's capabilities, accelerating progress towards SoftBank 2.0. It aims to invest in businesses and foundational platforms that SoftBank believes to revolutionize and innovate the world tomorrow.

SoftBank Vision Fund

Temasek Holdings is a lender provider. The company offers debt financing and focuses on transforming economies, increasing middle-income populations, developing comparative advantages, and emerging champions. Financial services, transportation, industrial, consumer, real estate, telecommunications, media, technology, and life sciences are among the industries served by the firm.

Temasek Holdings

GIC is a global investment firm established in 1981 to manage Singapore's foreign reserves. A disciplined long-term value investor, GIC is uniquely positioned for investments across a wide range of asset classes, including equities, fixed income, private equity, real estate, and infrastructure. GIC invests through funds and directly in companies, partnering with its fund managers and management teams to help world-class businesses achieve their objectives. In tech investing, GIC seeks to be a lifetime partner to the companies it invests in. GIC has investments in over 40 countries around the world. Headquartered in Singapore, GIC employs over 1,700 people across 10 offices in key financial cities worldwide.

SambaNova Systems

SambaNova Systems develops software and hardware solutions for artificial intelligence and machine learning applications. It creates systems that support data processing and model training. Their technology focuses on various computing tasks. SambaNova serves sectors including healthcare, finance, and autonomous vehicles.

SambaNova Systems provides AI hardware and integrated systems to run AI applications in data centers and the cloud. The company’s flagship solution, Dataflow-as-a-Service is a subscription-based hardware platform that provides pre-trained deep-learning models for production-ready deployments. It can be used to run natural language processing (NLP) models and process true-resolution images and 3D sensor data.

The toolkit to build machine learning applications at scale

Machine Learning Infrastructure

SambaNova Systems is an AI innovation company specializing in supplying hardware and integrated systems for running AI applications in data centers and cloud environments. It claims that its platform is the first to offer a completely integrated system designed specifically for AI, encompassing enterprise-grade chips, software, and models.

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

SambaNova Systems provides AI hardware and integrated systems to run AI applications in data centers and the cloud. The company specializes in pre-trained deep-learning models for production-ready deployments.

Foundation Models

Powering Innovation – The CEO of SambaNova Systems praises Saudi Investment in AI

Hugging Face

To promote the integration, both companies will host a hackathon in December to provide developers with hands-on experience using the new deployment system. The partnership allows developers to deploy text-only and multimodal chatbots in minutes instead of hours using SambaNova Cloud's API and Hugging Face's Spaces platform.

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

SambaNova Systems provides AI hardware and integrated systems to run AI applications in data centers and the cloud. The company’s flagship solution, Dataflow-as-a-Service is a subscription-based hardware platform that provides pre-trained deep-learning models for production-ready deployments. It can be used to run natural language processing (NLP) models and process true-resolution images and 3D sensor data.The company also offers an integrated software and hardware system to train and deploy foundation models, deep learning, and AI-accelerated workloads. DataScale’s large on-chip and system memory enables it to handle large models and data that cannot be handled by graphics processing units (GPUs). DataScale is powered by a seven-nanometer Cardinal SN30 Reconfigurable Data Unit (RDU) which has also delivered a world record in GPT training that was up to 6x faster than DGX A100 AI systems (built on the NVIDIA A100 Tensor Core GPU). In September 2023, it launched its latest chip, the <a href="https://sp-edge.com/updates/21988">SN40L</a>, which powers its full-stack large language model (LLM) platform, the SambaNova Suite.The company also offers software to extract, optimize, and execute the optimal dataflow graph of models for training, inference, data analytics, and high-performance computing. In addition, it offers state-of-the-art open-source models as well as models pre-trained by SambaNova, including their GPT offering. These models can be fine-tuned on a company's data for greater accuracy.Key customers and partnershipsAs of January 2023, the company served customers in the financial services and insurance, healthcare and life sciences, manufacturing and auto, oil, gas, and energy, retail and e-commerce, and public sectors. In May 2023, SambaNova collaborated with Together to develop BLOOMChat, a 176-billion-parameter multilingual chat LLM for commercial use cases. It was trained on 46 languages and developed by an international collaboration of more than 1,000 researchers.Funding and financialsIn April 2021, the company raised USD 676 million in a Series D funding round led by SoftBank Vision Fund 2 at a valuation of more than USD 5 billion. The funds were utilized to expand its customer base primarily in the data center market.

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 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

SambaNova Systems is an AI innovation company specializing in supplying hardware and integrated systems for running AI applications in data centers and cloud environments. It claims that its platform is the first to offer a completely integrated system designed specifically for AI, encompassing enterprise-grade chips, software, and models.Its two main products are DataScale and SambaNova Suite. DataScale is an integrated software and hardware system that utilizes the Reconfigurable Dataflow Architecture (RDA) and allows for the customization, development, and deployment of advanced large language models (LLMs), computer vision models, and models for scientific exploration. Its other key offering, the SambaNova Suite, is an integrated GenAI platform that allows users to create their own LLMs that can compete with GPT-4 and other models. Notably, customers maintain perpetual ownership of the adapted models. SambaNova Suite incorporates SambaNova's proprietary SN40L AI chip (manufactured by Taiwan Semiconductor Manufacturing Co) and is claimed by the company to surpass the performance of NVIDIA's chips.In <a href="https://sp-edge.com/updates/33514">September 202</a>4, the company introduced SambaNova Cloud, an AI inference platform to implement GenAI workflows and runs Meta's Llama 3.1 405 billion and Llama 3.1 70 billion model. Previously in <a href="https://sp-edge.com/updates/21988">September 2023</a>, SambaNova Suite introduced new features, including Llama2 variants, a highly accurate multilingual model (BLOOM 176B), and improved document retrieval embeddings, resulting in reduced total cost of ownership (TCO) for AI models due to enhanced LLM inference efficiency. The firm also unveiled its <a href="https://sp-edge.com/updates/21988">new chip, the SN40L</a> manufactured by TSMC, which will power its full-stack LLM platform, the SambaNova Suite.&nbsp;SambaNova Systems' unique business model involves building servers and AI software and leasing these to companies on a subscription basis rather than selling its chips. This approach allows clients to leverage advanced AI capabilities without the need for in-house machine learning expertise.Key customers and partnershipsNotable customers include SoftBank, Accenture, Los Alamos National Laboratory, and Analog Devices.In&nbsp;<a href="https://sp-edge.com/updates/35721">November 2024</a>, the company partnered with Hugging Face to launch an integration that simplifies ChatGPT-like interface deployment through a single-click process.&nbsp;&nbsp;&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.

SambaNova Systems provides AI hardware and integrated systems to run AI applications in data centers and the cloud. The company specializes in pre-trained deep-learning models for production-ready deployments.Its flagship offering, dataflow-as-a-serviceTM, overcomes the limitations of legacy technology to power the large complex foundation models that enable customers to discover new services and revenue streams and boost operational efficiency.In February, <a href="https://sp-edge.com/updates/27353">SambaNova Systems </a>released a new large language model (LLM) Samba-1 composed of more than 50 top-grade AI models for customized enterprise usage.&nbsp;

<div>
 
 AI21 is an Israel-based AI research lab developing large language models (LLMs). The firm also builds GenAI applications based on its LLMs, marketing them to businesses and consumers.&nbsp;
 
 
 AI21 launched its first AI model, &ldquo;Jurassic-1,&rdquo; in August 2021, offering two versions. The larger variant, Jurassic-1 Jumbo, contained 178 billion parameters&mdash;three billion more than OpenAI&rsquo;s 175-billion parameter GPT-3 model. Similar to GPT-3, Jurassic is able to write emails and articles, summarize text, compose poetry and recipes, create website layouts, and generate code.&nbsp;
 
 
 The firm concurrently launched AI21 Studio, a platform allowing users to train custom versions of Jurassic-1 and embed them into products via an API.&nbsp;
 
 
 In May 2022, AI21 confirmed it was working on a new AI system, called the &ldquo;modular reasoning knowledge and language&rdquo; or &ldquo;MRKL&rdquo; framework (pronounced &ldquo;miracle&rdquo;). MRKL augments LLMs, connecting to external sources and symbolic reasoning models to enable the generation of accurate historical information, news on current events, and dynamic information, such as weather, exchange rates, and Wikipedia information. This allows models to accurately answer math queries by calling a calculator and navigate more complex questions by breaking down queries into parts. An initial implementation of MRKL, Jurassic-X, is available on AI21 Studio, which allows users to connect LLMs to their own databases and navigate their data using natural language.
 
 
 In March 2023, the firm launched &ldquo;Jurassic-2,&rdquo; a successor to its initial language model. The new LLM differs from Jurassic-1 and most popular LLMs, in that it incorporates semantic reasoning into its text generation processes alongside statistical inference, enabling the model to more reliably and accurately respond to queries.
 
 
 AI21 says this was achieved by training Jurassic-2 in two phases: A traditional self-supervised phase using an extensive corpus of unstructured and unlabeled data and a second phase, involving a large volume of labeled data to teach the model to follow instructions. Jurassic-2 did not initially implement the MRKL framework, although AI21 confirmed it as an upcoming feature.
 
 
 The company claims that its foundation models are 30% more efficient than those of other providers and it also does not charge additional fees for the use of fine-tuned models.
 
 
 
 
 In March 2024,
 <a href="https://sp-edge.com/updates/27995">
 AI21 launched Jamba,
 </a>
 a model that integrates the Mamba Structured State Space model (SSM) technology and transformer components. The company further introduced 
 <a href="https://sp-edge.com/updates/32879">
 Jamba 1.5 Mini and Jamba 1.5 Large
 </a>
 to offer high performance and efficiency for long-context language processing in August 2024. The models have a hybrid architecture combining Transformer and Mamba approaches, allowing for quality responses with large context windows.
 
 
 Key customers and partnerships
 
 
 As of June 2023, AI21&rsquo;s customers include Latitude, Easyway, Verb, Tweet Hunter, and Harambee.
 
</div>

AI21 Labs

UK-based Stability AI is actively involved in building AI applications and offers a range of foundation models, including:Text-to-image modelStable Diffusion (SDXL 1.0): The open-source text-to-image model incorporates a dual network architecture with a 3.5-billion parameter base model and a 6.6-billion parameter refiner. The model was trained on image-caption pairs from the LAION-5B dataset derived from Common Crawl data. It excels in high-quality image generation, spatial object positioning, and complex concept recognition. The model can be fine-tuned for specific tasks using techniques such as embeddings, hypernetworks, and tools like DreamBooth, a deep-learning generation model.<a href="https://sp-edge.com/updates/30420">Stable Diffusion 3 Medium:</a> a text-to-image open-source AI models with 2 billion parameters utilizing a Diffusion Transformer Architecture and can be fine-tuned using small datasets.<a href="https://sp-edge.com/updates/32260">Stable Fast 3D:</a> Text-to-image model generates 3D images from a single 2D image.In November 2023, the company launched <a href="https://sp-edge.com/updates/23352">two new products</a> Sky Replacer and Stable 3D. Sky Replacer lets users manipulate the aesthetic of the sky in their photos from a choice of nine alternatives, enhancing the overall image appeal and Stable 3D aims to simplify the process of creating textured 3D objects, from images or text prompts, into a quick, automatic activity.Text-to-text modelsStable Beluga 1: The instruction-following language model is based on LLaMA 65 billion and has reasoning capabilities.Stable Beluga 2 (FreeWilly): An expansion to Stable Beluga 1, this model is based on LLaMA 70 billion and reportedly ranks near the top of the Open LLM Leaderboard.StableLM is an open-source language model suite; the company has released alpha versions of three billion- and seven-billion parameter models, with 15 to 65 billion-parameter models to follow. It's designed to generate text and code, and can power various downstream applications. <a href="https://sp-edge.com/updates/25750">Stable LM 2 1.6B, </a>an AI language model designed for multiple languages, was released in January 2024.The Japanese StableLM Alpha, is a seven-billion parameter Japanese language model, which claims to have superior performance compared to other publicly available Japanese language models. It offers text generation capabilities and is released under the Apache License 2.0 for commercial use, with an additional research version available for research purposes.StableCode has three billion parameters and is specifically designed to help programmers with coding tasks by providing autocomplete suggestions and responses to programming instructions.Text-to-audio modelStable Audio, which has 907 million parameters, uses a latent diffusion model architecture for audio and is conditioned on various factors including text metadata, audio file duration, and start time. This conditioning allows control over the content and length of the generated audio.Text-to-image model<a href="https://sp-edge.com/updates/26910">Stable Diffusion 3,</a> which has 800 million range and 8 billion parameters and combines a diffusion transformer architecture and flow matching. Additionally, the model can depict multi-subject prompts, create images, and correct spelling. <a href="https://sp-edge.com/updates/30068">Public preview</a> of this model was announced in June 2024.<a href="https://sp-edge.com/updates/26645">Stable Cascade,</a> a text-to-image model developed with a three-phase approach for image creation and modification.Text-to-video model<a href="https://sp-edge.com/updates/24289">Stable Video Diffusion</a>, an AI model designed to produce videos from images, offered as a research preview. The models, SVD and SVD-XT, can generate short, high-quality clips but come with limitations.<a href="https://sp-edge.com/updates/27695">Stable Video 3D (SV3D), </a>a GenAI tool to create 3D videos to create multi-view 3D models from a single input image and can produce short video content from image or text prompts.<a href="https://sp-edge.com/updates/31945">Stable Video 4D,</a> a model that enables users to upload video and obtain dynamic videos from different views.There has been considerable debate about the ethical and copyright implications of using stable diffusion to create images. The model is particularly permissive when it comes to creating different types of content, which has raised concerns about its potential for abuse. In response to its permissiveness, Stability AI has become involved in copyright infringement lawsuits, with artists and Getty Images raising legal objections to the use of their content in the model's training data.In March 2024, <a href="https://sp-edge.com/updates/27872">Stability AI's founder and CEO, Emad Mostaque, resigned from his role </a>and the company's board to focus on the development of decentralized AI to bring transparency and competitiveness to AI.In April 2024, the company made Stable Diffusion 3 and Stable Diffusion 3 Turbo available on the <a href="https://sp-edge.com/updates/28612">Stability AI developer platform API.</a>In May 2024, Stability AI <a href="https://sp-edge.com/updates/29321">introduced Stable Artisan,</a> a tool to enable media generation for Discord users.Key customers and partnershipsIn December 2022, Stability AI entered a partnership with Amazon, with AWS designated as the preferred cloud provider to facilitate the development and expansion of Stability AI's AI models.In March 2024,<a href="https://sp-edge.com/updates/27403"> Stability AI partnered with Tripo AI,</a> a provider of AI 3D models, to release TripoSR for 3D object reconstruction to cater to the demands of entertainment, gaming, industrial design, and architecture professionals, with responsive outputs for visualizing detailed 3D objects.In April 2024, the company<a href="https://sp-edge.com/updates/28612"> partnered with Fireworks AI,</a> a provider of API platforms, to deliver Stable Diffusion 3 and Stable Diffusion 3 Turbo for enterprises.In September 2024, the company <a href="https://sp-edge.com/updates/33262">launched Stable Image Ultra, Stable Diffusion 3 Large, and Stable Image Core</a>, its text-to-image models on Amazon Bedrock.

Stability AI

Cohere is a Canadian startup founded in 2019 by Aidan Gomez, Ivan Zhang, and Nick Frosst, with backgrounds in natural language processing and prior experience at Google Brain. The firm specializes in the development and deployment of large language models (LLMs) for various applications across enterprise and business use cases. Its foundation model, Cohere Command, is a large natural language text generation model with 52.4 billion parameters, focused on task-oriented dialogue, creating summarization, copywriting, dialogue extraction, and question answering.Cohere also provides Cohere Embed, a model designed to generate vector embeddings that capture the essence of text, improving capabilities in search, content moderation, and intent recognition. These embeddings help empower Cohere's multilingual customizable models, which can be fine-tuned to cater to specific use cases and industries. Additionally, Cohere ensures secure deployment options, including private cloud solutions, for added data security and privacy. In November 2023, Cohere unveiled <a href="https://sp-edge.com/updates/23446">Embed V3</a> with advanced capabilities in matching documents to queries, increasing the efficiency of retrieval augmented generation, and reducing the operational costs of LLM applications. In February 2024, the company introduced <a href="https://sp-edge.com/updates/26583">Aya,</a> an open-source LLM that supports 101 languages.According to Stanford University's HELM benchmarks, Cohere's Command model ranks among the highest-performing models available.In March 2024,<a href="https://sp-edge.com/updates/27502"> Cohere released an advanced language model, “Command-R,</a>” for enterprises. The model offers improved performance on retrieval augmented generation (RAG) and tool usage, with longer context windows of up to 128,000 tokens.In April 2024, <a href="https://sp-edge.com/updates/28198">the company released an advanced language model, Command R+</a>, for business applications. The model offers enhanced retrieval augmented generation (RAG) with citation, supports 10 business languages, and automates workflows. Additionally, <a href="https://sp-edge.com/updates/28463">Cohere also released Rerank 3,</a> a model designed to enhance enterprise search and RAG systems. In the same month, <a href="https://sp-edge.com/updates/28509">the company also introduced a private beta for Cohere Compass,</a> a foundation embedding model designed to allow multi-aspect data indexing and searching, and also <a href="https://sp-edge.com/updates/28789">launched a toolkit available for developers to build AI applications</a> faster, offering production-ready applications that can be deployed across cloud providers, with enhanced security and customization options.In May 2024, Cohere introduced <a href="https://sp-edge.com/updates/29350">Command R Fine-Tuning</a> for enhanced performance for business application workload and<a href="https://sp-edge.com/updates/29761"> released Aya 23, </a>a multilingual language model capable of handling 23 languages,available in 8 billion and 35 billion parameters.<a href="https://sp-edge.com/updates/34141">In September 2024</a>, Cohere released updated versions of its APIs for its AI models Chat, Embed, Rerank, and Classify. These updates, collectively called “API V2,” introduced several upgrades to its existing models, including mandatory model version specification in API calls, consolidation of input parameters for Chat API, and improved tool integration capabilities.&nbsp;Key customers and partnershipsIn November 2021, Cohere partnered with Google Cloud to leverage its infrastructure support and TPUs for product development and deployment. Cohere also partnered with other major cloud providers like AWS and Oracle.In March 2024,<a href="https://sp-edge.com/updates/27307"> Cohere partnered with consultancy firm Accenture</a> to integrate its Command model and retrieval augmented generation (RAG) capabilities to offer GenAI solutions for businesses.In April 2024, <a href="https://sp-edge.com/updates/28932">Cohere partnered with Amazon </a>to incorporate Command R+ and Command R to Amazon's cloud platform, Bedrock.In June 2024, the company<a href="https://sp-edge.com/updates/30492"> partnered with Borderless AI,</a> a provider of AI-powered HR solutions, to create tailored AI agents for HR tasks.The company entered into a <a href="https://sp-edge.com/updates/31052">strategic partnership with i-5O,</a> a provider of AI solutions for manufacturing, as part of Cohere's Startup Program and also partnered with <a href="https://sp-edge.com/updates/31590">Fujitsu</a> in July 2024 to develop a Japanese LLM.In September 2024, Cohere <a href="https://sp-edge.com/updates/33458">partnered with Nomura Research Institute (NRI)</a>, a Japanese consulting firm, to develop the NRI Financial AI Platform.

Cohere

Founded in 2022, Hippocratic AI is a healthcare-focused AI model developed by Health GPT. At its core, Hippocratic AI uses a state-of-the-art (SOTA) large language model (LLM) designed to improve healthcare processes, particularly in non-diagnostic tasks. Hippocratic AI aims to differentiate itself from traditional LLMs by prioritizing pre-training with trusted, evidence-based healthcare content rather than the broader Internet. Claimed to be the first safety-focused LLM for healthcare, the model undergoes a unique Reinforcement Learning with Human Feedback process, known as RLHF-HP, which involves working with healthcare professionals to validate its readiness for use. In addition, the model aims to incorporate a compassionate “bedside manner” in its interactions with patients, recognizing the impact of empathy on emotional wellbeing and health outcomes.According to the company, Hippocratic AI outperformed GPT-4 in majority of tests and certifications. Out of 114 evaluations, it outperformed GPT-4 in 105 cases, with a notable margin of +5% in 74 evaluations and +10% in 43 certifications.Key customers and partnerships&nbsp;In August 2023, the company launched the Hippocratic AI Founding Partner Program, an initiative through which the company collaborates with leading healthcare organizations to become founding partners and actively participate in the development and validation of Hippocratic AI's LLM and technology. The program includes establishing use cases, ensuring clinical and patient safety, and contributing to the advancement of healthcare-specific AI applications. In February 2024, these companies began <a href="https://sp-edge.com/updates/27145">beta</a> testing their LLM for non-diagnostic applications in healthcare.In March 2024, <a href="https://sp-edge.com/updates/27696">Hippocratic AI partnered with NVIDIA</a> to develop AI healthcare agents that have low-latency conversational interactions with patients.

Hippocratic AI

<div>
 
 Founded in 2023, GenHealth.ai is a startup focused on advancing healthcare solutions through the use of GenAI. Its proprietary approach involves training a foundation transformer model, known as DOOG-E, on extensive healthcare data, including 50+ million of coded patient claims and clinical information. DOOG-E is a specialized Generative Pre-Trained Transformer (GPT) AI designed for healthcare applications, with 70 million parameters and one billion tokens. Unlike traditional large language models, DOOG-E is a large medical model (LMM) that uses medical events such as ICD, CPT, RxNorm, and LOINC codes as its &quot;language&quot; to predict future sequences of health events based on historical data.
 
 
 The company claims that its LMM, trained on medical data, is less prone to bias and hallucination compared to its GenAI, large language models (LLM), rendering it more dependable for healthcare applications.
 
 
 Funding and financials&nbsp;
 
 
 In July 2023, the company raised USD 13 million in early funding co-led by Craft Venture and Obvious Ventures. It planned to use the funds to support the development and expansion of its LMM for various healthcare applications, including risk adjustment, care management, and financial benchmarking.
 
 
 
</div>

GenHealth

Foundation models that can handle a range of natural language processing (NLP) use cases. Typical tasks include generating summaries, translating, answering questions, and classifying text. These models typically use text inputs and generate text outputs.

Fine-tuned versions of large language models, which are focused on specific tasks and applications (e.g. code generation, medical event prediction, financial NLP tasks, etc). These are usually developed by training LLMs using custom data and also serve as foundation models that can be developed even further. These models typically use text inputs and can generate text and/or code outputs.

Foundation models that translate visual data based on features and contextual information identified during training. This enables models to interpret images and video, applying those interpretations to predictive or decision-making tasks. Typical tasks include image recognition and classification into categories. These models typically use image and/or video inputs and generate text outputs.

Foundation models that are trained to understand and work with two or more forms of input data (e.g., text and images) to solve problems and complete tasks using both natural language processing and computer vision. These models can also generate outputs across textual and visual modalities. Typical tasks include visual question answering, image captioning, and generating images based on text descriptions. These models typically use text and/or visual inputs and generate text and/or visual outputs.

Foundation models that use big data to suggest or recommend additional products to consumers. These models are designed to predict user-item interaction probabilities and provide recommendations to users. The models are trained to make these inferences based on historical data on customer interactions and non-interactions. These models typically use user features, item features and user interactions as inputs, and generate numeric values like ratings predictions and matching probabilities as outputs.

Foundation models that are capable of automatic speech recognition, transcription in multiple languages, and translation from these languages to English. These are sometimes referred to as audio models. These models typically use speech/audio as inputs and generate text outputs.

Foundation models that transform user text prompts into video clips.

Foundation models that generate music from text descriptions.

All companies within the space are building large AI models

Companies in this space leverage NLP to train LLMs

The hub exclusively covers companies that have built foundation models

All companies within the space can leverage their foundation models for generative AI applications

The technology enables the creation of personalized content

PROMINENT_CATEGORY

<div>
 Artificial Intelligence platforms, SambaNova and Hugging Face have announced an integration aiming to simplify the deployment of interfaces similar to ChatGPT. This is achievable through an efficient single-click process.
 This cooperative effort allows developers to swiftly deploy text-centric and multimodal chatbots in a significantly reduced duration, from hours to mere minutes. This is made possible using the API of SambaNova Cloud and Spaces platform by Hugging Face. The integration facilitates the utilization of powerful models such as the Llama 3.2-11 billion-Vision-Instruct, with an impressive demonstration of processing speeds reaching 358 tokens per second.
 In an effort to advocate the integration, both firms are set to host a hackathon event in December. This platform will be intended to accord developers with first-hand experience in using this novel deployment system.
</div>

SambaNova Systems

About EDGE

Contact Us

Resources

Area of Focus

Technology Research Made Effortless