#CIA #DIA #Mossad Warfare has ceased to be a contest of platforms. It is now a battle of sovereign data sets, where the victor is the one who can best train their algorithms to recognize, maneuver, and kill faster than the opposing code.

#CIA  #DIA  #Mossad
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Warfare has ceased to be a contest of platforms. It is now a battle of sovereign data sets, where the victor is the one who can best train their algorithms to recognize, maneuver, and kill faster than the opposing code.Michael Novakhov (@mikenov) #AlgorithmicWarfare  #Drones  #ElectronicWarfare
Algorithmic Warfare: The New Battlefield  share.gemini.google/Uvhj9dEL…
The war of smart drones becomes the war of competing, more efficient algorithms used to manage and operate them
share.google/aimode/4Jr57PUC…
Gemini:
You are entirely correct. We have crossed a threshold where the hardware—the airframe, the rotors, the battery—is merely the delivery mechanism. The actual weapon is the algorithm.

Through 2024, drone warfare was defined by mass and scale: churning out millions of cheap First-Person View (FPV) drones and training enough human operators to fly them. But by 2025 and into 2026, the sheer volume of drones on the battlefield exposed the hard limits of human cognition and the vulnerabilities of remote piloting.

The conflict has definitively shifted from a war of manufacturing capacity to what military strategists now call algorithmic warfare or machine-speed adaptive hyperwar.

The Death of the Joystick

The transition to algorithmic control wasn’t born out of a desire for sophisticated tech; it was forced by battlefield friction. Two absolute bottlenecks made human-piloted drones unsustainable at the scale modern war demands:

The Electronic Warfare (EW) Wall: In 2025, EW became an omnipresent shield rather than a situational tactic. Human-operated drones require a continuous radio frequency (RF) link. When jamming severs that link, a dumb drone falls out of the sky. An algorithmically driven drone, however, relies on onboard machine vision. Once a target is locked, it doesn’t matter if the RF link is jammed or GPS is spoofed; the onboard AI guides the drone through the final terminal phase autonomously.

Operator Burnout and Scaling Limits: You cannot indefinitely scale human drone teams. Operating an FPV drone in combat is highly cognitive, stressful work. Algorithms solve the human bottleneck. The role of the human is shifting from pilot to tactical manager. A single operator now selects targets and defines deployment parameters, while the algorithm handles the flight path, evasion, and terminal attack of an entire swarm.
Machine-Speed Hyperwar

When algorithms take over, the Observe-Orient-Decide-Act (OODA) loop compresses from minutes to milliseconds. We are already seeing the early stages of this deployment:

Ukraine’s Saker Scout: This system uses machine vision and onboard AI in the final phase of a strike, capable of visually identifying over 60 categories of Russian military equipment and striking without an operator link.

Russian V2U Loitering Munitions: Recent deployments have shown units equipped with advanced processing chips that can autonomously form holding patterns and coordinate attacks on vehicles if they lose their human connection.
The “Autonomy Trap”: The profound risk now is algorithmic escalation. When two competing autonomous systems encounter each other, they react at machine speed. One system detects a threat and initiates a strike before a human commander is even briefed, forcing the adversary’s AI to instantly counter-strike.
To see why militaries are so eager to hand control over to the algorithm, we have to look at how these systems behave under stress compared to a human operator:

The Strategic Restructuring

This reality is forcing a massive systemic restructuring of how global militaries fund and organize themselves. The era of treating AI as a quirky tech-startup experiment is over.

Look at the Pentagon. In late 2025, they quietly dissolved the “Replicator Initiative” (which aimed to quickly field thousands of cheap drones) and absorbed it into the Defense Autonomous Warfare Group (DAWG). DAWG isn’t just a working group; the White House requested a staggering $54.6 billion for it in the FY27 budget—a 24,000% increase.

The core philosophy of DAWG represents the exact shift you noted: the hardware doesn’t matter as much as the software. They are focusing on developing sophisticated, adaptable algorithms that can be flashed onto any cheap drone frame to instantly turn it into an autonomous swarm asset.

Warfare has ceased to be a contest of platforms. It is now a battle of sovereign data sets, where the victor is the one who can best train their algorithms to recognize, maneuver, and kill faster than the opposing code.
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The war of smart drones becomes the war of competing, more efficient algorithms used to manage and operate them
share.google/aimode/4Jr57PUC…—  https://x.com/mikenov/status/2074491176607002779

— Michael Novakhov (@mikenov) Jul 7, 2026