Search “NVIDIA”

NVIDIA releases AIOps platform Minerva

On October 22, 2026, NVIDIA released Minerva, an AIOps platform for AI factories. According to NVIDIA's official blog, the platform collects telemetry data from infrastructure and AI workloads, then uses dedicated AI models to turn the data into actionable insights; it builds a dynamic knowledge graph that maps GPUs, SuperNICs, switches, cables, and the logic of the jobs running on them, analyzes billions of data points per hour, learns normal behavior, detects unseen anomalies, and predicts failures. The platform includes a built-in AI assistant that can connect to external agent tools and supports troubleshooting cluster health and providing remediation suggestions in natural language. IREN, IBM, Jio, Lambda, Tesla, and others plan to deploy it, while Dell, Lenovo, and Supermicro will incorporate it into their AI factory operations product portfolios. On the same day, Unite.AI reported that Minerva includes a multi-agent AI assistant named Sherlock and provides an MCP server, and that IREN, Bitdeer AI, and others are already using it. There are currently no subsequent developments.

NVIDIA releases AIOps platform Minerva

On October 22, 2026, NVIDIA released Minerva, an AIOps platform for AI factories. According to NVIDIA's official blog, the platform collects telemetry data from infrastructure and AI workloads, then uses dedicated AI models to turn the data into actionable insights; it builds a dynamic knowledge graph that maps GPUs, SuperNICs, switches, cables, and the logic of the jobs running on them, analyzes billions of data points per hour, learns normal behavior, detects unseen anomalies, and predicts failures. The platform includes a built-in AI assistant that can connect to external agent tools and supports troubleshooting cluster health and providing remediation suggestions in natural language. IREN, IBM, Jio, Lambda, Tesla, and others plan to deploy it, while Dell, Lenovo, and Supermicro will incorporate it into their AI factory operations product portfolios. On the same day, Unite.AI reported that Minerva includes a multi-agent AI assistant named Sherlock and provides an MCP server, and that IREN, Bitdeer AI, and others are already using it. There are currently no subsequent developments.

View story:NVIDIA releases AIOps platform Minerva

Aravind Srinivas shares JOLT post-training research in collaboration with NVIDIA

Aravind Srinivas shared JOLT, a post-training method proposed by Perplexity in collaboration with NVIDIA. The method lets the same model serve as both teacher and student, and trains the teacher to learn from rewards from its own attempts while penalizing drift away from the student's behavior. On the MATH benchmark, JOLT reaches accuracy comparable to GRPO with 6.5 times fewer training tokens; JOLT+ additionally provides outcome-based rewards to the student model and clearly surpasses GRPO on math, coding, terminal tasks, and tool-use benchmarks. Currently this research is being shared publicly by Aravind Srinivas, with no further follow-up progress yet.

Aravind Srinivas shares JOLT post-training research in collaboration with NVIDIA

Aravind Srinivas shared JOLT, a post-training method proposed by Perplexity in collaboration with NVIDIA. The method lets the same model serve as both teacher and student, and trains the teacher to learn from rewards from its own attempts while penalizing drift away from the student's behavior. On the MATH benchmark, JOLT reaches accuracy comparable to GRPO with 6.5 times fewer training tokens; JOLT+ additionally provides outcome-based rewards to the student model and clearly surpasses GRPO on math, coding, terminal tasks, and tool-use benchmarks. Currently this research is being shared publicly by Aravind Srinivas, with no further follow-up progress yet.

View story:Aravind Srinivas shares JOLT post-training research in collaboration with NVIDIA

NVIDIA Releases Relational Foundation Model Kumo Relational

On October 22, 2026, NVIDIA released Kumo Relational, a pretrained relational foundation model that can make predictions directly on enterprise databases in a single forward pass, without task-specific training, feature engineering, or table flattening. According to the same release, across 41 tasks on 15 databases—RelBench V1/V2, SAP SALT, and 4DBInfer—the model outperformed supervised relational deep learning models and gradient-boosted tree pipelines with expert feature engineering; on SAP SALT, its MRR was 8% higher than the AutoGluon ensemble. The model is available through NVIDIA's open-source GPU-native structured-data-models library or NVIDIA NIM, and supports databases with 500B+ rows. There are currently no subsequent independent development facts.

View story:NVIDIA Releases Kumo Relational, a Relational Foundation Model

NVIDIA releases OpenShell reference architecture

On October 21, 2026, NVIDIA released the OpenShell reference architecture for building, isolating, observing, and enforcing secure agents on enterprise infrastructure and edge systems; the architecture is now available. The architecture uses Vera Rubin to run model inference, Vera CPU to host the agent harness, and BlueField-4 DPU to run Sentry for chip-level policy enforcement; Sentry can isolate out-of-bounds agents at millisecond latency. On the same day, NVIDIA released Sentry, a security software framework that monitors AI agents and enforces access policies within a hardware-isolated trust domain on the BlueField-4 DPU, without relying on host software; the framework is part of the OpenShell reference architecture announced at GTC Berlin and is planned to be opened early next year. Subsequently, Red Hat and Nvidia expanded their collaboration, planning to integrate the OpenShell reference architecture as a native capability into its AI platform, and to provide runtime security controls, model access governance, and hardware support for autonomous AI agents through Red Hat AI Factory with Nvidia.

NVIDIA releases OpenShell reference architecture

On October 21, 2026, NVIDIA released the OpenShell reference architecture for building, isolating, observing, and enforcing secure agents on enterprise infrastructure and edge systems; the architecture is now available. The architecture uses Vera Rubin to run model inference, Vera CPU to host the agent harness, and BlueField-4 DPU to run Sentry for chip-level policy enforcement; Sentry can isolate out-of-bounds agents at millisecond latency. On the same day, NVIDIA released Sentry, a security software framework that monitors AI agents and enforces access policies within a hardware-isolated trust domain on the BlueField-4 DPU, without relying on host software; the framework is part of the OpenShell reference architecture announced at GTC Berlin and is planned to be opened early next year. Subsequently, Red Hat and Nvidia expanded their collaboration, planning to integrate the OpenShell reference architecture as a native capability into its AI platform, and to provide runtime security controls, model access governance, and hardware support for autonomous AI agents through Red Hat AI Factory with Nvidia.

View story:NVIDIA releases OpenShell reference architecture

Nvidia unveils five-layer AI architecture

On October 21, 2026, Nvidia unveiled a five-layer AI architecture during its keynote at GTC Berlin 2026. NVIDIA founder and CEO Jensen Huang described AI as a five-layer structure consisting of energy, AI factories, models, and applications, and said the world has reached the starting point of a new industrial revolution. According to an on-site update published the same day on the NVIDIA Blog, Huang also mentioned that European companies including L'Oréal, Revolut, Spotify, Merck, Vodafone, Zara, Porsche, Nestlé, and HSBC are working with NVIDIA to advance AI, and said NVIDIA has invested nearly $10 billion in Europe's technology ecosystem and collaborates with more than 12,000 partners. The next day, The Elec reported that the architecture is called the "Five-Layer Cake," with the five layers being, in order: power and energy infrastructure; accelerated computing hardware; AI factory infrastructure (including neoclouds and communications networks); AI models covering domains such as language, biology, chemistry, physics, robotics, and animation; and an application layer that connects tokens to industries and enterprises. Huang called on Europe to build a complete five-layer architecture of its own and to shift from being an AI consumer to an AI producer. There are currently no subsequent developments.

View story:Nvidia unveils five-layer AI architecture at GTC Berlin

NVIDIA expands open-source Agent Toolkit and launches Agent Knowledge Foundation

On October 21, 2026, NVIDIA announced the expansion of its open-source Agent Toolkit and the launch of the Agent Knowledge Foundation. According to information published by the NVIDIA Newsroom that day, the expansion also adds the OpenShell secure runtime, the NemoClaw blueprint, and tools such as NeMo Relay and NeMo Compass. The Agent Knowledge Foundation includes CUDA-X libraries and the new Auto-Ontology library, and integrates the Nemotron Retriever and the Kumo family of open models, allowing enterprises to use it without migrating data or rebuilding existing workflows. The same source said that companies such as Palantir, Databricks, and Snowflake have already integrated the toolkit into their respective platforms. There are currently no subsequent independent developments.

NVIDIA releases time series forecasting model Kumo Forecast

NVIDIA has released the time series forecasting model Kumo Forecast (formerly NV-Tesseract Forecasting). The model uses MOMENT-1-large as its backbone, employing an encoder of approximately 340 million parameters plus a trainable forecasting head, with the encoder weights kept frozen. Its DARR mode retrieves patterns from historical data via k-nearest neighbors and fuses them with direct forecasting results; it also provides an interpretable framework that outputs lag and feature attributions by forecast step. The model is released under the Apache 2.0 license and supports input sequence lengths from 256 to 2048. There are currently no subsequent developments.

View story:NVIDIA releases Kumo Forecast time series forecasting model

Mistral AI and NVIDIA partner to develop AI-native engineering workflows

On October 21, 2026, Mistral AI announced a partnership with NVIDIA to bring AI into the field of industrial engineering. According to Testing Catalog, the collaboration includes faster simulation, open benchmarks and accompanying datasets for physical AI, and evaluation of agentic AI in CAE and EDA scenarios. In addition, Mistral's models will be integrated into the NVIDIA Omniverse libraries for GPU-accelerated 3D scene generation. The partnership is currently at the announcement stage, with no further progress disclosed.

View story:Mistral AI and NVIDIA partner to develop AI-native engineering workflows

Databricks and NVIDIA bring RFD4-Proteina to Genesis Workbench

Databricks and NVIDIA plan to integrate NVIDIA BioNeMo's open-source protein design model RFD4-Proteina into Databricks' Genesis Workbench. According to a Databricks blog post dated October 21, 2026, the model will run on the generally available AI Runtime serverless NVIDIA GPU compute. RFD4-Proteina can simultaneously generate protein sequences and all-atom structures, and supports optional reward-guided search that steers candidate designs toward target properties such as thermostability and binding affinity. Genesis Workbench includes two built-in RFD4-Proteina workflows, Antibody Design and Vaccine Design, and can be extended through Genie Code and NVIDIA BioNeMo Agent Toolkit skills. No further progress has been disclosed at this time.

View story:Databricks and NVIDIA Bring RFD4-Proteina to Genesis Workbench

Nvidia releases open-weight models for enterprise agents and PCs

On October 19, 2026, Nvidia released open-weight models for always-on agents and edge computing. According to TechCrunch AI, the Nemotron 3.5 Super VL is a 120-billion-parameter enterprise-grade agent model, which Nvidia says can achieve accuracy comparable to Nemotron 3 Ultra on instruction-following and tool-calling tasks; two lightweight Bolt models are designed to run locally on AI PCs equipped with RTX Spark chips and on DGX Spark workstations. The report said Super VL and Nemotron 3.5 Bolt 74B-A9B 24GB are already available, and the smallest Bolt E4B will launch later this month. On October 21, Nvidia announced an expansion of its open model portfolio covering language, robotics, biology and quantum computing, positioned around European sovereign intelligence; the portfolio includes Nemotron 3.5 Super VL and Nemotron 3.5 Bolt, among others. The report said Super VL is now available on Hugging Face, ModelScope, OpenRouter and build.nvidia.com, and Bolt E4B 4GB is expected to be available on October 23.

English translation is being prepared.

On October 19, 2026, Nvidia released open-weight models for always-on agents and edge computing. According to TechCrunch AI, the Nemotron 3.5 Super VL is a 120-billion-parameter enterprise-grade agent model, which Nvidia says can achieve accuracy comparable to Nemotron 3 Ultra on instruction-following and tool-calling tasks; two lightweight Bolt models are designed to run locally on AI PCs equipped with RTX Spark chips and on DGX Spark workstations. The report said Super VL and Nemotron 3.5 Bolt 74B-A9B 24GB are already available, and the smallest Bolt E4B will launch later this month. On October 21, Nvidia announced an expansion of its open model portfolio covering language, robotics, biology and quantum computing, positioned around European sovereign intelligence; the portfolio includes Nemotron 3.5 Super VL and Nemotron 3.5 Bolt, among others. The report said Super VL is now available on Hugging Face, ModelScope, OpenRouter and build.nvidia.com, and Bolt E4B 4GB is expected to be available on October 23.

View story:Nvidia releases open-weight models for enterprise agents and PCs

NVIDIA announces global telecom operators are turning networks into distributed intelligent platforms

On October 21, 2026, NVIDIA announced at GTC Berlin that multiple telecom operators worldwide are extending NVIDIA accelerated computing to central offices, metro sites and base stations, turning networks into distributed intelligent platforms. Reports the same day show that T-Mobile, together with NVIDIA and Nokia, completed an AI-RAN call on a commercial network in Bellevue, Washington; BT, Deutsche Telekom, Elisa and Orange are conducting live network trials based on Nokia's CUDA-accelerated anyRAN software and NVIDIA Aerial RAN Computer. NVIDIA also launched two configurations, ARC MGX 2U and MGX 4U, for high-capacity sites, and Nokia and Cisco have integrated the Nemotron open model into their respective network automation software. Other reports say nearly 20 operators have announced AI-RAN collaborations based on Nokia anyRAN software and NVIDIA Aerial RAN Computer; BT and Deutsche Telekom plan to conduct live network trials in 2027, and Elisa is already running voice, mobile data and video analytics simultaneously in a live 5G spectrum environment.

Nvidia unveils five-layer AI architecture at GTC Berlin

On October 21, 2026, Nvidia unveiled a five-layer AI architecture during its keynote at GTC Berlin 2026. NVIDIA founder and CEO Jensen Huang described AI as a five-layer structure consisting of energy, AI factories, models, and applications, and said the world has reached the starting point of a new industrial revolution. According to an on-site update published the same day on the NVIDIA Blog, Huang also mentioned that European companies including L'Oréal, Revolut, Spotify, Merck, Vodafone, Zara, Porsche, Nestlé, and HSBC are working with NVIDIA to advance AI, and said NVIDIA has invested nearly $10 billion in Europe's technology ecosystem and collaborates with more than 12,000 partners. The next day, The Elec reported that the architecture is called the "Five-Layer Cake," with the five layers being, in order: power and energy infrastructure; accelerated computing hardware; AI factory infrastructure (including neoclouds and communications networks); AI models covering domains such as language, biology, chemistry, physics, robotics, and animation; and an application layer that connects tokens to industries and enterprises. Huang called on Europe to build a complete five-layer architecture of its own and to shift from being an AI consumer to an AI producer. There are currently no subsequent developments.

NVIDIA Releases Kumo Relational, a Relational Foundation Model

On October 22, 2026, NVIDIA released Kumo Relational, a pretrained relational foundation model that can make predictions directly on enterprise databases in a single forward pass, without task-specific training, feature engineering, or table flattening. According to the same release, across 41 tasks on 15 databases—RelBench V1/V2, SAP SALT, and 4DBInfer—the model outperformed supervised relational deep learning models and gradient-boosted tree pipelines with expert feature engineering; on SAP SALT, its MRR was 8% higher than the AutoGluon ensemble. The model is available through NVIDIA's open-source GPU-native structured-data-models library or NVIDIA NIM, and supports databases with 500B+ rows. There are currently no subsequent independent development facts.

NVIDIA releases Kumo Forecast time series forecasting model

NVIDIA has released the time series forecasting model Kumo Forecast (formerly NV-Tesseract Forecasting). The model uses MOMENT-1-large as its backbone, employing an encoder of approximately 340 million parameters plus a trainable forecasting head, with the encoder weights kept frozen. Its DARR mode retrieves patterns from historical data via k-nearest neighbors and fuses them with direct forecasting results; it also provides an interpretable framework that outputs lag and feature attributions by forecast step. The model is released under the Apache 2.0 license and supports input sequence lengths from 256 to 2048. There are currently no subsequent developments.

Mistral AI and NVIDIA partner to develop AI-native engineering workflows

On October 21, 2026, Mistral AI announced a partnership with NVIDIA to bring AI into the field of industrial engineering. According to Testing Catalog, the collaboration includes faster simulation, open benchmarks and accompanying datasets for physical AI, and evaluation of agentic AI in CAE and EDA scenarios. In addition, Mistral's models will be integrated into the NVIDIA Omniverse libraries for GPU-accelerated 3D scene generation. The partnership is currently at the announcement stage, with no further progress disclosed.

Databricks and NVIDIA Bring RFD4-Proteina to Genesis Workbench

Databricks and NVIDIA plan to integrate NVIDIA BioNeMo's open-source protein design model RFD4-Proteina into Databricks' Genesis Workbench. According to a Databricks blog post dated October 21, 2026, the model will run on the generally available AI Runtime serverless NVIDIA GPU compute. RFD4-Proteina can simultaneously generate protein sequences and all-atom structures, and supports optional reward-guided search that steers candidate designs toward target properties such as thermostability and binding affinity. Genesis Workbench includes two built-in RFD4-Proteina workflows, Antibody Design and Vaccine Design, and can be extended through Genie Code and NVIDIA BioNeMo Agent Toolkit skills. No further progress has been disclosed at this time.