New York State is quietly becoming one of the most important nodes in the emerging AI-powered space economy. While California dominates headlines, New York's space sector, over 160 companies employing roughly 40,000 people, is undergoing a significant transformation driven by artificial intelligence and machine learning. This transformation is happening across three distinct fronts: commercial startups using AI to turn satellite data into actionable intelligence, defense contractors embedding AI into electronic warfare and communications systems, and a growing academic infrastructure that is building the computer and talent base to sustain it all.
This report profiles the six Empire Space Census companies with explicit AI connections, identifies additional companies in the Census quietly adopting AI tools, maps the academic and institutional network available to support this ecosystem, and provides a deep dive into the ANDRO Marconi-Rosenblatt AI & ML Innovation Lab, one of the most significant and underappreciated AI research assets in the state.
The central finding is this: New York's AI-space ecosystem is real, growing, and under-networked. The companies, universities, and the federal infrastructure exist. What is missing is a deliberate connection between them.
Part 1: Why AI and Space Are Converging Now
Space has always required autonomy. The Apollo Guidance Computer made real-time navigation decisions faster than any human pilot could. What has changed is the scale and sophistication of that autonomy. As the Balerion Space research team put it in their 2025 report AI in Orbit, space is already a world of drones, and AI is critical to managing a world of drones. Every satellite, lander, and station module is an unmanned machine. Autonomy is not a feature, it is the baseline requirement.
The three converging forces that are accelerating this are:
The constellation explosion. SpaceX's Starlink operates over 6,000 satellites. Manual management of a fleet that size is physically impossible. Collision avoidance, orbital slot management, and signal routing are all handled by AI. Every operator building a constellation at scale will face this same reality.
The data deluge. Modern Earth observation satellites generate more imagery per day than human analysts could review in a year. AI is the only mechanism capable of processing this at speed and converting raw pixels into intelligence. Companies like Capella Space and BlackSky have built their entire business models around this premise.
The shift to edge autonomy. Deep space adds a constraint that makes AI non-negotiable: the speed of light. A signal to Mars takes 20 minutes one way on average. A rover, a habitat, or a manufacturing platform operating on Mars cannot wait 40 minutes for a human to make a decision. AI must operate locally, in real time, without a connection to Earth.
The defense analogy is instructive. Anduril Industries built its approach around Lattice OS, a software layer that fuses sensor data and coordinates autonomous systems to give operators a unified, real-time operational picture across many assets.did not strictly start as a hardware company. It started by building a software nervous system, Lattice OS and layered hardware around it. Lattice OS allows a single operator to manage large numbers of autonomous assets simultaneously, with full situational awareness. Rather than treating software and hardware as separate layers, it tightly integrates both into a single system of autonomy and sensing. The space economy is moving in a very similar direction: satellites, orbital tugs, factories, and stations all managed as a coherent, AI-orchestrated system.
Part 2: The Six Census Companies with AI Connections
Ursa Space Systems
Location: Ithaca, NY (Finger Lakes)
Employees: ~39
Website: ursaspace.com
What they do: Ursa Space is a satellite intelligence company founded in 2014 at Cornell University. They built what they call a "Virtual Constellation", a platform that ingests data from dozens of other commercial satellite operators (SAR, optical, infrared, RF) and runs AI analytics on top of it to produce actionable intelligence reports. Rather than owning satellites, Ursa owns the analytical layer that sits above them. Their platform can answer natural language queries like "analyze maritime activity in the Gulf of Aden for ship-to-ship transfers" and return a structured intelligence report in minutes rather than hours.
How they use AI: Ursa's core product is built on machine learning. Their algorithms process synthetic aperture radar (SAR) imagery, which looks static to the human eye and extract meaningful patterns: ship movements, construction activity, industrial output, environmental changes. In 2025, they partnered with AWS and Element 84 to build a generative AI layer on top of their geospatial platform, making satellite intelligence accessible to non-expert users for the first time. They have also integrated AI-driven scheduling to optimize which satellites should collect which data at what time.
Partners and customers: U.S. Space Force (multiple contracts), U.S. Combatant Commands, National Geospatial-Intelligence Agency (NGA), Aireon (air traffic data integration), NEC Japan (SAR analytics), NUVIEW (LiDAR), SkyFi, SI Imaging Services, Umbra, MAIAR Ltd (UK defense), Sumitomo Corporation (exclusive Japan distribution deal, 2025). Total funding: $59M, including a $10M venture loan from Horizon Technology Finance.
Why they matter for NY: Ursa is the most commercially mature AI-space company in the state. Their customer list reads like a who's who of defense and intelligence. The Ithaca location, close to Cornell, gives them access to top research talent. Their generative AI pivot in 2025 is significant: it signals that satellite intelligence is moving toward more accessible, query-based interfaces.
ANDRO Computational Solutions
Location: Rome, NY (Mohawk Valley / Griffiss Park)
Employees: ~38
Website: androcs.com
What they do: ANDRO is a 30-year-old research and engineering company headquartered at the Griffiss Business and Technology Park in Rome, NY, the same campus as the Air Force Research Laboratory Information Directorate (AFRL/RI). They specialize in wireless communications, electronic warfare, signals intelligence, and AI/ML integration, with a primary customer base in the U.S. military. In 2019, ANDRO launched the Marconi-Rosenblatt AI & ML Innovation Lab (covered in depth in Part 4), which has become the engine of their AI work.
How they use AI: ANDRO's AI applications are primarily in the RF/signals domain using machine learning to identify, classify, and respond to radio frequency signals in real time. Their flagship product DeepSPEC® uses deep learning to perform electronic support (threat detection, identification, and mitigation) at the edge meaning on the device, without a cloud connection. This is critical for contested electromagnetic environments where latency is a matter of mission success or failure. They are also developing RF-Gen, an AI system that generates synthetic RF training data for Army electronic warfare systems, and RANGER, an autonomous counter-radar capability for unmanned aircraft.
Partners and customers: DARPA, U.S. Army (multiple contracts including a multimillion-dollar RF-Gen contract in 2025), U.S. Navy (SBIR contract for RANGER), U.S. Special Operations Command (USSOCOM), Air Force Research Laboratory, Deepwave Digital, Ettus Research / National Instruments. ANDRO is also adjacent to the Innovare Advancement Center ecosystem.
Why they matter for NY: ANDRO sits at the intersection of two critical capabilities for the space sector: AI and RF communications. Space systems are fundamentally RF-dependent satellites that communicate via radio signals, and protecting those signals from jamming and interference is a top national security priority. ANDRO's expertise in AI-driven spectrum management is directly applicable to space communication security.
Agileview
Location: New York City
Employees: ~9
Website: agileview.ai
What they do: Agileview is a computer vision company focused on making satellite, aerial, and drone imagery more accessible and useful for government and commercial organizations. Their platform processes geospatial imagery and applies computer vision models to extract structured intelligence detecting objects, tracking changes, and simulating scenarios for defense and intelligence applications.
How they use AI: Computer vision is the core of their operations. Agileview trains models to detect and classify objects in satellite and aerial imagery, enabling clients to automate what would otherwise require large teams of human analysts. They also offer simulation capabilities for modeling complex defense and intelligence scenarios allowing customers to test hypotheses against synthetic environments before committing to real-world action.
Partners and customers: Government and defense organizations. Specific customers are not publicly disclosed, consistent with the nature of their work.
Why they matter for NY: Agileview represents a small but technically sophisticated player in the computer vision / geospatial intelligence space. As a NYC-based company, they have access to the city's deep AI talent pool and proximity to major defense and intelligence contractors.
SpaceKnow
Location: New York City
Employees: ~2 (NY office)
Website: spaceknow.com
What they do: SpaceKnow is a satellite analytics company that applies AI and machine learning to satellite imagery to produce economic and industrial intelligence. Their flagship products track industrial activity, factory output, shipping traffic, energy consumption at a global scale. They are most well known for their China Satellite Manufacturing Index, which tracks industrial activity across Chinese manufacturing facilities and has been cited by major financial institutions as an independent economic indicator.
How they use AI: SpaceKnow uses deep learning models trained on large volumes of satellite imagery to detect and quantify economic activity. Their platform monitors thousands of locations globally and delivers automated reports on activity changes. They also offer API access for clients who want to integrate satellite-derived economic signals into their own models.
Partners and customers: Financial institutions, hedge funds, government agencies, and corporations seeking independent economic intelligence. SpaceKnow's data products have been integrated into financial analysis workflows at major investment firms.
Why they matter for NY: SpaceKnow illustrates the financial services application of AI-powered space data a natural fit for New York's status as a global finance capital. Their work demonstrates that satellite AI is not just a defense tool but a commercial intelligence product with broad industry applications.
Wallaroo AI
Location: New York City
Employees: ~49
Website: wallaroo.ai
What they do: Wallaroo is an AI/ML deployment and operations platform, essentially infrastructure software for running machine learning models in production at scale. They serve industries including aerospace and defense, providing the technical backbone that allows organizations to deploy, monitor, and update AI models efficiently.
How they use AI: Wallaroo's product is the infrastructure layer that other AI applications run on. In the aerospace and defense context, they enable rapid deployment of AI models for real-time decision-making for satellite operations, predictive maintenance, autonomous systems, and more. Their platform addresses a critical bottleneck: the gap between training a model in a research environment and deploying it reliably in a production environment.
Partners and customers: Aerospace and defense firms, government agencies. Their platform has specific use cases called out for aerospace and defense on their website.
Why they matter for NY: Wallaroo occupies a different but essential layer of the AI stack. While companies like Ursa and Agileview are building AI applications for space, Wallaroo provides the operational infrastructure those applications need to run reliably. They represent the "picks and shovels" opportunity in AI-space convergence.
Palantir (NYC Office)
Location: New York City
Employees: ~608 (NYC)
Website: palantir.com
What they do: Palantir is one of the largest and most influential data analytics and AI companies in the world, with a major and growing presence in space. Their NYC office houses a substantial portion of their workforce. Their core product, Palantir Foundry, integrates and analyzes massive, heterogeneous datasets to produce operational intelligence.
How they use AI: Palantir's space application MetaConstellation is a platform that unifies access to commercial satellite constellations, allowing operators to task multiple satellites from different vendors through a single interface. The platform uses AI to optimize collection, fuse data from different sources, and deliver actionable intelligence rapidly. Palantir Foundry has been contracted by the U.S. Space Force for command and control, processing orbital data and tasking assets. In the language of the Anduril/Lattice OS analogy: Palantir is building the command layer for the space economy.
Partners and customers: U.S. Space Force, U.S. Army, Intelligence Community, commercial space operators, NATO allies. Palantir is one of a handful of companies with direct access to classified government space programs.
Why they matter for NY: Palantir's NYC presence brings serious scale and influence to the state's AI-space ecosystem. Their MetaConstellation platform is arguably the most ambitious attempt to build the AI orchestration layer for commercial and government space operations. Their proximity to New York's financial sector also opens pathways for commercial applications of space intelligence.
Part 3: Additional Census Companies Adopting AI
Beyond the six explicitly identified companies, a review of the Empire Space Census reveals a number of organizations that are either already adopting AI tools or are well-positioned to do so. These companies were not flagged as AI companies in the Census, but they show meaningful AI adjacency.
C3.AI (NYC, ~48 employees) C3.AI is an enterprise AI software company with an explicit aerospace application: AI-driven aircraft readiness. Their NYC presence connects the state's AI infrastructure to aerospace maintenance and logistics. C3.AI's platform monitors equipment health, predicts failures, and optimizes maintenance scheduling directly applicable to satellite ground systems and launch infrastructure.
SAIC (Western NY, ~227 employees) Science Applications International Corporation has flagged its space portfolio as including Space Data and AI capabilities. Their Western NY presence supports Air and Space Force programs, bringing federal AI investment into the state's upstate corridor. SAIC is actively integrating AI into space systems engineering, virtual training, and robotics.
VegaMX (NYC, ~50 employees) VegaMX works in aerospace and defense data analysis and won a 2021 Air Force Hyperspace Challenge award, a competitive program for novel space and defense technologies. Their work combines satellite data with analytics for both agricultural and defense applications.
NearSpace Labs (NYC, ~17 employees) NearSpace Labs democratizes access to high-resolution aerial and near-space imagery with a focus on urban challenges, climate resilience, flood mapping, and infrastructure monitoring. Their platform has strong AI analytics components and addresses some of the same market segments as Ursa Space.
Floodbase / Cloud to Street (NYC, ~27 employees) Uses satellite imagery, combined with AI models, to provide parametric flood insurance, an innovative application of space data that directly impacts climate risk. Strong overlap with the emerging space-data-as-insurance-product market.
Arbol (NYC, ~56 employees) Also uses satellite data to power parametric climate insurance. Backed by Space Capital. Arbol demonstrates how New York's financial services industry is becoming a downstream customer for AI-processed satellite intelligence.
Kayrros (NYC) Advanced energy and environmental geoanalytics using satellite data. Clients include major energy companies and government agencies. Strong AI component in their methane monitoring and energy infrastructure tracking products.
Orbital Insight (NYC) A subsidiary of Privateer. Uses AI to derive economic and geopolitical insights from orbital data, tracking activity at ports, factories, and military installations. One of the original companies to commercialize AI-driven satellite imagery analysis.
Grammatech (Southern Tier, ~100 employees) Develops advanced software security platforms for aerospace and defense. Their work on software assurance and vulnerability detection for aerospace systems is increasingly AI-assisted, making it relevant to securing the software stacks of space systems.
Huntington Ingalls Industries (Central NY, ~87 employees) HII brings its electronic warfare expertise to protecting space-based assets. Their Central NY presence, adjacent to the AFRL ecosystem, positions them to integrate AI-driven EW capabilities into space domain awareness.
Part 4: Deep Dive ANDRO Marconi-Rosenblatt AI & ML Innovation Lab.
Rome, NY | Founded: 2019 | Parent: ANDRO Computational Solutions
Background and Origin
In 2019, ANDRO Computational Solutions, a 25-year-old defense-focused research firm headquartered at the Griffiss Business and Technology Park in Rome, NY, launched the Marconi-Rosenblatt Artificial Intelligence and Machine Learning Innovation Lab. The name is deliberate: Guglielmo Marconi pioneered radio communications, and Frank Rosenblatt invented the perceptron, the foundational building block of neural networks. The lab sits at precisely that intersection.
The lab was established with $1 million in New York State CFA grant funding, matched by a $1 million company capital investment, and was fast-tracked by approximately $5 million in federal research contracts at launch. It is led by co-directors Dr. Jithin Jagannath (Chief Scientist/CTO, Founding Director) and Dr. Anu Jagannath (Chief Scientist/CRO). Dr. Jithin Jagannath holds an adjunct appointment at the University at Buffalo's Department of Electrical Engineering and is an IEEE Senior Member and recipient of the 2021 IEEE Region 1 Technological Innovation Award.
What the Lab Does
The Marconi-Rosenblatt Lab's work sits at the intersection of four technical domains:
RF Machine Learning (RFML). The lab's most distinctive capability. They apply deep learning to the radio frequency spectrum, training neural networks to detect, classify, identify, and respond to wireless signals in real time. Applications include:
1 - Automatic modulation classification (identifying signal types without prior knowledge)
2 - RF fingerprinting (uniquely identifying devices from their signal characteristics, the wireless equivalent of a fingerprint)
3 - Spectrum anomaly detection (identifying jamming, spoofing, or interference)
4 - Electronic support (threat detection and identification at the tactical edge)
Their DeepSPEC product is the commercial manifestation of this work, an AI-driven electronic support system demonstrated at the Army's Cyber Quest 2025 experiment.
Autonomous Unmanned Systems. The lab develops AI for uncrewed aircraft systems (UAS), with a focus on human-machine teaming. Their RANGER program (Robust Autonomy for Negation of Enemy Radar), funded by the U.S. Navy applies AI to enable autonomous counter-radar capabilities, allowing unmanned aircraft to detect, analyze, and evade or neutralize enemy radar systems without human intervention. Their earlier work on the RF-HAWK program produced a novel UAS payload that performs the functions of multiple specialized sensing units in a single integrated package.
Synthetic Data Generation. Their RF-Gen project, funded by a multimillion-dollar U.S. Army contract in 2025, addresses one of the most critical bottlenecks in military AI: the lack of high-quality training data. RF-Gen uses generative AI to produce synthetic radio frequency datasets that realistically simulate contested electromagnetic environments. This allows Army AI systems to be trained and tested without requiring expensive and restricted real-world RF data collection. The project supports the Army's Project Linchpin initiative and has direct implications for electronic warfare readiness.
Networked AI / Multi-Agent Systems. The lab developed the MR-iNet Gym (Marconi-Rosenblatt Framework for Intelligent Networks), an open-source architecture for building and testing multi-agent reinforcement learning solutions for distributed wireless networks. This framework allows researchers to simulate and optimize how multiple AI-enabled nodes (satellites, ground stations, aircraft) communicate and coordinate in complex RF environments. It has been published in top IEEE and Elsevier journals and is available to the broader research community.
The lab has produced over 40 peer-reviewed publications in journals including IEEE Communications Surveys & Tutorials, Computer Networks (Elsevier), and IEEE Communications Magazine, plus 18 patents (granted and pending). Recent highlights include a 2025 IEEE Communications Surveys & Tutorials paper on Graph Neural Networks for IoT and NextG Networks, an open-source RF fingerprinting dataset for Bluetooth and WiFi devices, and multiple book chapters in Springer and Wiley-IEEE series on deep learning for unmanned systems and wireless communications.
Is ANDRO a Resource for Other NY Space Companies?
Yes, with appropriate caveats. ANDRO's work is primarily classified or ITAR-sensitive, which limits open collaboration. However, several pathways exist:
Open-source tools: MR-iNet Gym is publicly available and usable by any organization working on networked AI systems.
Academic bridge: Dr. Jagannath's UB appointment creates a channel through which academic and industry partners can access expertise without engaging ANDRO directly on classified work.
CFA grant model: The state grant mechanism that funded the lab's launch is available to other NY companies. ANDRO's success with this model is a template.
Innovare Advancement Center: ANDRO is located within the Griffiss ecosystem, which includes the Innovare Advancement Center, an open, unclassified research campus designed specifically to facilitate collaboration between defense contractors, academia, and startups. This is the most practical pathway for other NY space companies to access the Griffiss/ANDRO ecosystem.
Part 5: Academic and Institutional AI Network
New York has one of the strongest academic AI ecosystems in the world, but very little of that capacity has been deliberately connected to the space sector. The following institutions represent the highest-value targets for network-building.
Empire AI Consortium
The Empire AI Consortium is New York State's most significant AI infrastructure investment. Launched in 2024 with over $400 million in public-private funding, Empire AI is housed at the University at Buffalo and provides shared high-performance GPU computing to member institutions. Current members include SUNY, CUNY, Columbia, Cornell, NYU, RPI, University of Rochester, and the Flatiron Institute. The system's first machine (Alpha) is already running at capacity with over 350 researchers. A second, more powerful machine (Beta) powered by NVIDIA Blackwell chips is in development.
Space relevance: Empire AI is currently focused on health, climate, and education research but the computer infrastructure is domain-agnostic. There is no structural reason why space AI applications satellite image processing, orbital simulation, RF signal classification could not be run on Empire AI resources. Building a formal space research track within Empire AI would be a high-leverage move.
Air Force Research Laboratory Information Directorate (AFRL/RI)
Located at Griffiss Business and Technology Park in Rome, the same campus as ANDRO AFRL/RI, is one of the most important federal AI research institutions in the country. With approximately 838 employees and an annual economic impact estimated at over $500 million for the five-county area, AFRL/RI focuses on C4I (Command, Control, Communications, Computers, and Intelligence), cyber, and information technologies. It maintains active partnerships with industry (including ANDRO) and academic institutions.
Space relevance: AFRL/RI is the bridge between academic AI research and operational military space applications. Companies in the NY space ecosystem that want defense contracts for AI-space applications should be building relationships here. The Innovare Advancement Center was specifically created to make this collaboration easier.
Cornell University
Ithaca is home to both Cornell University and Ursa Space Systems (founded by Cornell alumni), the Cornell Lab of Ornithology (a world leader in machine learning applied to observational data, a methodology directly applicable to satellite data analysis), and strong programs in computer science, electrical engineering, and aerospace. Cornell is an Empire AI founding member and has deep ties to the NYC startup ecosystem through Cornell Tech on Roosevelt Island, as well as the Cornell AI Innovation Hub.
New York University
NYU is home to the CILVR Lab led by Yann LeCun (Meta's Chief AI Scientist and one of the three "Godfathers of Deep Learning") and the Center for Data Science. NYU received $20 million from NSF in 2023 to establish the AI Institute for Artificial and Natural Intelligence (ARNI). NYU's robotics and autonomous systems programs have direct relevance to space autonomy applications.
Rensselaer Polytechnic Institute (RPI)
RPI is a founding Empire AI member and is the closest major research university to the Griffiss/AFRL/ANDRO ecosystem in Rome. RPI has longstanding research relationships with AFRL/RI and strong programs in computational science, electrical engineering, and materials science (relevant to aerospace manufacturing). RPI's proximity to both Albany and the Mohawk Valley makes it a natural connector institution.
University at Buffalo (SUNY)
UB is the host institution for Empire AI and is home to the Kostas Research Institute, which received a $7.4 million National Spectrum Consortium award for advanced spectrum coexistence research directly in ANDRO's domain. Dr. Jithin Jagannath of the Marconi-Rosenblatt Lab holds an adjunct appointment here, creating a direct institutional link between ANDRO's applied research and UB's academic infrastructure.
Griffiss Institute and Innovare Advancement Center
While not a traditional academic institution, the Griffiss Institute operates the Innovare Advancement Center in Rome, an open, unclassified research campus purpose-built to connect defense contractors, startups, and academia. Innovare houses quantum labs, UAS testing facilities, and collaborative workspaces. It is the physical infrastructure through which the Griffiss/AFRL/ANDRO ecosystem is made accessible to outside partners. The HUSTLE Defense Accelerator, operated by the Griffiss Institute, provides seed funding for AI, ML, cyber, quantum, and UAS startups.
GENIUS NY Accelerator
Operated by CenterState CEO and funded by Empire State Development, GENIUS NY is the world's largest accelerator for uncrewed systems, automation, and advanced air mobility startups. It invests $3 million annually in five finalist companies (with one $1M grand prize, and four $500K award recipients). Since 2017, GENIUS NY companies have raised over $350 million in follow-on funding. GENIUS NY teams regularly engage with the Innovare Advancement Center and the broader Griffiss AI ecosystem.
Part 6: Economic Impact and Ecosystem Assessment
Current State
New York's space sector employs approximately 40,000 people across 160+ companies. Of these, fewer than 15 have been identified as actively using or building AI tools as a core part of their space-related business. This is not because the rest are indifferent to AI, it is because most of the Census is composed of precision manufacturers and aerospace component suppliers whose AI journey is at an earlier stage, focused on process automation, quality control, and predictive maintenance rather than the satellite analytics and autonomous systems applications that dominate the AI-space conversation.
The AI-intensive companies are concentrated in two geographic clusters:
New York City: Palantir, Agileview, SpaceKnow, Wallaroo, Arbol, NearSpace Labs, Floodbase, Kayrros, and Orbital Insight- a cluster of data and analytics companies leveraging NYC's AI talent base and financial sector connections.
Mohawk Valley / Griffiss corridor: ANDRO, AFRL/RI, BAE Systems Rome, Huntington Ingalls, and CACI- a cluster of defense-focused AI companies embedded in the federal research infrastructure.
Between these two clusters, the Finger Lakes (Ursa Space, Cornell, L3Harris) serves as a connector.
The Opportunity Gap
The most significant gap in the NY space AI ecosystem is not capability, it is connectivity. The following disconnects are limiting growth:
NYC analytics companies don't know the Mohawk Valley defense AI companies. Ursa Space and Palantir are building AI platforms for space intelligence. ANDRO is building AI for the RF/communications layer that makes those platforms work. These companies should know each other, and probably don't.
The Empire AI computer is not being used for space research. New York has invested $400M+ in AI computer infrastructure. None of it is currently directed at space applications. A formal space research track within Empire AI, seeded by a partnership between Cornell/Ursa, UB/ANDRO, and NYU would be a concrete first step.
GENIUS NY and Griffiss are not formally connected to the NYC space AI cluster. The accelerator and the defense AI infrastructure in upstate New York operate largely independently from the commercial space analytics and data companies in the city.
Manufacturing companies are not yet AI-adopters. The roughly 100 precision manufacturers in the Census, concentrated on Long Island and in Western NY represent a large untapped opportunity for AI-driven quality control, predictive maintenance, and supply chain optimization. Programs like NYU's ARNI, RPI's computational science group, or SUNY's manufacturing extension programs could serve as translators.
Conclusion
Artificial intelligence is not a future condition for the New York space sector. It is a present reality, already embedded in the state's most sophisticated space companies from Ursa Space's satellite intelligence platform to ANDRO's battlefield-ready RF machine learning systems to Palantir's orbital command layer. What New York has not yet done is knit these capabilities into a coherent, self-reinforcing network.
The assets are exceptional. The Marconi-Rosenblatt Lab is doing world-class research at the intersection of AI and wireless communications. Ursa Space is one of the leading satellite intelligence companies in the country. Empire AI is building compute infrastructure that no other state can match. Cornell, NYU, and RPI are producing AI talent that major tech companies are actively recruiting.
The next step is not building more, it is connecting what exists. A deliberate effort to map, introduce, and align these assets would position New York not just as a participant in the AI-space revolution, but as one of its defining centers.