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AI avatars are digital character designed to mimic human-like qualities created through computer-generated imagery (CGI) and various AI technologies such as, natural language processing (NLP), synthetic voice generation, computer vision, and emotion AI. They can represent real people, digital beings, or objects, often used for branding or interactive purposes. What sets these AI avatars apart is their ability to have personalized interactions with users based on their behavior, preferences, and past history. Additionally, they have multilingual capabilities, making them accessible and user-friendly to a global audience. These avatars are commonly used in virtual reality, video games, online forums, and as virtual assistants.

• NVIDIA ACE
  4.3

  3 Reviews

Gartner defines cloud AI developer services (CAIDS) as cloud-hosted or containerized services and products that enable software developers who are not data science experts to use artificial intelligence (AI) models via APIs, software development kits (SDKs) or applications. Core capabilities include automated machine learning (autoML) including automated data preparation, automated feature engineering and automated model building, and model management and operationalization for language, vision and tabular use cases. Optional and important complementary capabilities include AI code models and assistants. Cloud AI developer services help organizations embed intelligence, such as AI and ML insights, into their applications. While that is what cloud AI developer services offer, it is more important to note how they accomplish this. These services democratize and increase the availability of AI and ML to software engineers through the automation and features offered. Traditional activities regarding data acquisition, data quality, feature engineering, algorithm selection and model training are augmented by the technology. Cloud AI developer services open up a world of possibilities for software engineers to build AI and ML production capabilities and features for enterprise-built applications.

• NVIDIA NGC
  4.5

  2 Reviews

Reviews for 'Data Center - Others'

• Mellanox Adapters
  5.0

  1 Review

The data center and cloud networking vendors covered in this market provide hardware and/or software solutions to deliver connectivity primarily within enterprise data centers. This includes data center core/spine switches, access switches (top of rack [ToR], leaf), virtual switching, Ethernet fabrics, network operating systems (NOSs) and network overlays, and the requisite management, automation and orchestration of those components.

• Cumulus NetQ
  4.7

  3 Reviews
• Mellanox Switches
  4.6

  54 Reviews
• 2 more products

Gartner defines file and object storage platforms as software and/or hardware platforms that offer object and distributed file system technologies for storing and managing unstructured data over NFS, SMB and Amazon S3 access protocols. File and object storage platforms store, secure, protect and scale an organization’s unstructured data with access over the network using protocols such as NFS, SMB and Amazon S3. Use cases include analytics, workload consolidation, backup and archiving, hybrid cloud, object-native applications, cloud IT operations, and high-performance files.

• SwiftStack (Legacy)
  4.6

  22 Reviews

Edge AI refers to the use of AI techniques embedded in IoT endpoints, gateways and edge servers, that can process and store data close to where it’s generated. While predominantly focused on AI inference, more sophisticated systems may include a local training capability to provide in-situ optimization of the AI models. This is done by constantly monitoring AI models and autoscaling them to match demands. Edge AI systems can reduce latency and data transport consumption, improve local processing capabilities thus find usage in applications ranging from autonomous vehicles to streaming analytics.

• NVIDIA EGX Platform
  4.7

  3 Reviews

Generative AI (GenAI) engineering refers to the field of engineering that focuses on the development, implementation and optimization of generative AI models. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. By developing GenAI models, engineers can create new and innovative ways to generate content. The vendors in this segment are made up by incumbent and startup vendors covering full-model life cycle management, specifically adjusted to and catering to development, refinement and deployment of generative models (e.g., LLMs) and other GenAI artifacts in production applications. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.

• NVIDIA DGX Cloud
  4.4

  3 Reviews

Generative AI (GenAI) Infrastructure providers are infrastructure vendors (such as cloud platforms and hardware manufacturers) that offer underlying technology, tools and hardware that other companies and developers use to build and deploy specific generative AI applications in production. Generative AI refers to technologies that can generate new derived versions of content, strategies, designs and methods by learning from large repositories of original source content. These providers offer scalable, reliable and cost-effective solutions for generative AI projects, which can be complex and expensive to train and deploy. Generative AI infrastructure providers focus on research and developing the foundational AI techniques, while application developers focus on building products using those foundational technologies. Please note that this market is based on Beta research and is continuously evolving. We will be making changes as and when there are new updates.

• NVIDIA DGX Cloud
  4.0

  1 Review