Trinity Ventures is an early stage venture capital firm dedicated to partnering with passionate entrepreneurs to transform revolutionary ideas into reality. With over $1 billion under management, Trinity Ventures believes in personal engagement, mutual respect and goal alignment with the entrepreneurs. Trinity focuses on early stage and seed technology investments with particular emphasis on social commerce and entertainment, digital media, Saas, and cloud and infrastructure.    Trinity Ventures has invested in such leading companies as Aruba Networks, 21Vianet, Blue Nile, LoopNet, Photobucket, SciQuest, Starbucks, BeachMint, Infoblox, Trion Worlds and Zulily.

Trinity Ventures

Bloomberg Beta is an early-stage venture capital firm with $375M under management, capitalized solely by Bloomberg. The fund exists to expand Bloomberg’s horizons by investing in companies built by extraordinary founders that make business work better, with a focus on machine intelligence.

Bloomberg Beta

Gaingels is a venture investment syndicate in service of the LGBT+ community and its allies, investing in companies with LGBT+ founders and C-suite leaders at all stages of growth, as well as in more established companies resolved on building more inclusive teams, with a global portfolio of 130+ companies and $70M in deployed investment capital to date.  The Gaingels network also actively supports its portfolio in identifying and recruiting diverse talent to their C-suite and board leadership teams and fosters a vibrant global community of industry leaders, investors, operators, and entrepreneurs who share a common goal for positive social change through business and successful investments.

Gaingels

Hack VC is an early-stage venture capital firm that invests in the cryptocurrency, fintech, and marketplaces sectors. The company was founded in 2017 and is headquartered in San Francisco, California, United States.

Hack VC

Coatue is a privately owned hedge fund sponsor. The firm invests in the public equity markets globally focusing on investments in technology, media, and telecommunications in addition to other sectors. It employs a long or short strategy to make its investments.

Coatue

Insight Partners is a global software investor that partners with growth-stage technology and software companies. Insight has a deep focus in Fintech, Cybersecurity, AI/ML, DevOps, and Healthcare sectors. Across their people and their portfolio, they encourage a culture around a core belief growth equals opportunity. As of December 31, 2022, the firm has over $75B in regulatory assets under management. Insight Partners has invested in more than 750 companies worldwide and has seen over 55 portfolio companies achieve an IPO.

Insight Partners

Felicis Ventures is a venture capital firm based in Menlo Park, California. The firm invests in seed through Series C stage companies across multiple sectors and industries reinventing core markets, as well as those creating frontier technologies. Felicis currently manages over $2B in capital across 8 funds. The firm is an early backer of more than 40 companies valued at $1B+. More than 90 of its portfolio companies have been acquired or gone public since the firm was founded by Aydin Senkut in 2006.

Felicis

Bond is a venture capital firm that supports visionary founders of high-growth Internet companies throughout their life cycle of innovation and growth. The firm, a spinout of the Kleiner Perkins Digital Growth Fund, was launched in January 2019 and founded by Mary Meeker with Mood Rowghani, Noah Knauf.

Bond

Weights & Biases

Weights & Biases offers performance visualization tools for machine learning. It helps companies turn deep learning research projects into deployed software by helping teams track their models, visualize model performance, and easily automate training and improving models.

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 toolkit to build machine learning applications at scale

Machine Learning Infrastructure

<div>Weights &amp; Biases (W&amp;B) is a developer-first MLOps (Machine-Learning Operations) platform that enables the collection and visualization of AI test results, facilitating engineers to compare different model versions more efficiently. The platform aids in the full lifecycle of machine-learning development, offering capabilities from tracking models, visualizing performance, and dataset versioning to automated training. A key characteristic of the platform is that it allows users to interrogate datasets used in model training, allowing for checks against biases and the presence of personally identifiable information before deployment.&nbsp;</div>

Empowering Tomorrow's Innovations with Generative AI Infrastructure

Generative AI Infrastructure

Weights & Biases Receives Recognition from Department of Defense’s Defense Innovation Unit

Amazon

To provide the Weights and Biases' platform to accelerate machine learning, deep learning, and AI development for Amazon SageMaker customers.

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

NVIDIA

To integrate Weights & Biases' MLops platform which plans and executes models with Run:ai's platform which orchestrates workloads on NVIDIA GPU.

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

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.

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

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.

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

<div>
 
 Weights &amp; Biases (W&amp;B) is a developer-first MLOps (Machine-Learning Operations) platform that enables the collection and visualization of AI test results, facilitating engineers to compare different model versions more efficiently. The platform aids in the full lifecycle of machine-learning development, offering capabilities from tracking models, visualizing performance, and dataset versioning to automated training. A key characteristic of the platform is that it allows users to interrogate datasets used in model training, allowing for checks against biases and the presence of personally identifiable information before deployment.&nbsp;
 
 
 The platform provides toolsets like 
 <a href="https://sp-edge.com/updates/19172">
 W&amp;B Weave and W&amp;B Production Monitoring
 </a>
 for creating and overseeing applications powered by data and machine learning with the help of interactive visual representations. Additionally, the company provides 
 <a href="https://sp-edge.com/updates/17880">
 W&amp;B Prompts
 </a>
 , a set of tools for tracking experiments debugging, and providing a one-click approach for evaluating and scoring prompts utilizing the OpenAI Eval framework.
 
 
 W&amp;B's platform is incorporated into 20,000 repositories as of August 2023, spanning various domains, including repositories for LLMs such as Langchain, LlamaIndex, and GPT4All, and key infrastructure providers like Coreweave, Lambda, and Graphcore.&nbsp;
 
 
 The W&amp;B platform is offered through a SaaS subscription model where users pay a monthly fee for a specified number of hours of platform use. W&amp;B features several packages, including a free version for personal accounts, USD 50 per month per user for teams (March 2024), and custom pricing packages for enterprises.
 
 
 Key customers and partnerships
 
 
 W&amp;B is utilized by multiple high-profile, well-funded GenAI model builders, including OpenAI, Aleph Alpha, Cohere, Anthropic, and Hugging Face. OpenAI, for instance, conducts all its model training using W&amp;B and it claims that its platform played a role in accelerating GPT-4 training. W&amp;B&rsquo;s customer base has increased 700,000 users from 100,000 in 2021, with more than 1,000 paying users as of August 2023.&nbsp;
 
 
 W&amp;B has formed strategic alliances with industry giants such as NVIDIA, Microsoft, AWS, GCP, Anyscale, and Snowflake.
 
 
 Funding and financials
 
 
 In
 <a href="https://sp-edge.com/updates/20874">
 August 2023
 </a>
 , the firm raised USD 50 million in a strategic round, bringing the total raised funds to USD 250 million. The funds were slated to finance the launch of Prompts, a new product aimed at monitoring and evaluating the performance of LLMs like OpenAI's GPT-4.&nbsp;
 
 
 
</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 develop and implement strategies, policies, and practices to ensure the responsible, secure, ethical, and safe use of Generative AI technologies within an organization.

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.

PROMINENT_CATEGORY

<div>
 FriendliAI, a company specialising in GenAI infrastructure, has entered into a partnership with Weights &amp; Biases. This alliance is aimed at simplifying the development and deployment process for developers dealing with GenAI models.
 Thanks to this collaboration, developers are enabled to apply the tools provided by Weights &amp; Biases while using the high-performance engine of FriendliAI in order to deploy AI models. The deployment of models is streamlined via dedicated endpoints, cutting out the necessity to load models manually. The goal of this partnership is to render workflows for machine learning developers more efficient by using FriendliAI's high-performing infrastructure for deploying models from the Weights &amp; Biases platform. 
 Friendli.ai offers GenAI infrastructure designed to assist businesses and developers in the utilisation of LLMs and additional AI models through various platforms, such as serverless endpoints, dedicated endpoints, and a deployable container solution. 
 
</div>

Weights & Biases

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