📌 TOPINDIATOURS Update ai: 10 drone swarms changing how modern air warfare is plan

AI-powered drone swarms are rapidly reshaping the nature of air power, shifting military advantage away from expensive platforms toward coordinated autonomy. AI now allows a large number of low-cost drones to operate as a unified system rather than individual assets.

These swarms can overwhelm traditional air defenses, adapt in real time, and continue missions even after sustaining losses. As major powers race to deploy them, AI drone swarms are emerging as one of the most disruptive forces in modern warfare.

1. Perdix

Perdix is among the earliest proof-of-concept drone swarms, demonstrating how small autonomous systems can work together as a cohesive unit. The micro-drones can self-organize, adapt when individual units fail, and continue missions without centralized control.

The system’s engineering breakthrough lies in its “distributed brain” architecture, in which each drone communicates and collaborates with others to maintain effectiveness even after losses.

Thanks to this design, the swarm can dynamically redistribute tasks and achieve a level of resilience that conventional military platforms have rarely displayed. It is built using commercial components. Perdix units have been produced at scale and proven reliable at extreme speeds, in cold temperatures, and under launch stresses.

2. Kargu-2

Kargu

Turkey’s STM developed Kargu-2, a 15-pound quadcopter designed to operate in coordinated swarms of up to 20 drones. It functions with AI-based object recognition, enabling autonomous strike capabilities.

The system has been widely cited as one of the first examples of AI-enabled drone swarms used in real combat, including deployments in Libya and the Armenia-Azerbaijan conflict.

Its onboard computer vision allows real-time detection and target tracking without external control, marking a significant step toward fully autonomous battlefield systems.

3. Pentagon’s Replicator Program

Pentagon’s Replicator program is pushing to scale autonomous drone swarms using low-cost, attributable systems. Led by the Defensive Innovation Unit, the effort is backed by $500 million in FY 2024 funding, with an additional amount of the same measure requested for FY 2025.

At the heart of Replicator are software frameworks like Autonomous Collaborative Teaming (ACT) and Opportunistic Resilient Network Topology (ORIENT). These platforms allow different drone types to coordinate as unified swarms, enabling a single operator to manage diverse autonomous systems.

4. Swarmer (Ukraine)

Ukraine’s war with Russia has accelerated the development of real-world drone swarm tactics, with the company Swarmer leading software innovation on the battlefield. Its systems enable coordinated operations of 3 to 25 drones per mission and have supported more than 100 documented combat deployments through 2025.

Swarmer helps reduce the human workload required to run complex UAV operations. It delegates real-time decisions to autonomous software, enabling a three-person team to manage missions that once required a group of nine operators.

5. Chinese Swarm I

Getty Images

China’s Sawrm I system showcases large-scale drone swarm coordination, with state media highlighting a demonstration involving up to 200 fixed-wing drones. It is launched from a mobile platform, with the system reportedly allowing a single operator to control a group of drones that can autonomously disperse and reorganize during flight.

Each drone is designed with onboard algorithms that can support peer-to-peer communication and coordinated movement without constant ground control. The system can also operate in controlled environments, using anti-jamming measures and local decision-making ot continue missions even when external signals go haywire.

6. Thales SwarmMaster

Thales

Thales’ SwarmMaster reflects Europe’s approach to drone swarm coordination, focusing on reducing operator workload through onboard AI rather than heavy centralized control.

Demonstrated under the COHESION platform in 2024, the system is designed to enable a single operator to oversee large drone groups while retaining human decision-making authority.

Its architecture embeds intelligent agents directly into each aircraft, enabling autonomous formation control, routing, and obstacle avoidance. By dividing tactical decisions between an onboard AI and a human supervisor, SwarmMaster aims to prevent operator overload, which can limit the effectiveness of traditional multi-drone missions.

7. Icarus Swarms

Icarus

Icarus Swarms has designed a modular autonomous swarm platform built around commercially available drone hardware. Introduced in 2021, the system focuses on scalable coordination of up to 50 drones for security, emergency response, and defense applications.

Its strength lies in flexible payload integration, allowing each drone to be qui…

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🔗 Sumber: interestingengineering.com

📌 TOPINDIATOURS Hot ai: Railway secures $100 million to challenge AWS with AI-nati

Railway, a San Francisco-based cloud platform that has quietly amassed two million developers without spending a dollar on marketing, announced Thursday that it raised $100 million in a Series B funding round, as surging demand for artificial intelligence applications exposes the limitations of legacy cloud infrastructure.

TQ Ventures led the round, with participation from FPV Ventures, Redpoint, and Unusual Ventures. The investment values Railway as one of the most significant infrastructure startups to emerge during the AI boom, capitalizing on developer frustration with the complexity and cost of traditional platforms like Amazon Web Services and Google Cloud.

"As AI models get better at writing code, more and more people are asking the age-old question: where, and how, do I run my applications?" said Jake Cooper, Railway's 28-year-old founder and chief executive, in an exclusive interview with VentureBeat. "The last generation of cloud primitives were slow and outdated, and now with AI moving everything faster, teams simply can't keep up."

The funding is a dramatic acceleration for a company that has charted an unconventional path through the cloud computing industry. Railway raised just $24 million in total before this round, including a $20 million Series A from Redpoint in 2022. The company now processes more than 10 million deployments monthly and handles over one trillion requests through its edge network — metrics that rival far larger and better-funded competitors.

Why three-minute deploy times have become unacceptable in the age of AI coding assistants

Railway's pitch rests on a simple observation: the tools developers use to deploy and manage software were designed for a slower era. A standard build-and-deploy cycle using Terraform, the industry-standard infrastructure tool, takes two to three minutes. That delay, once tolerable, has become a critical bottleneck as AI coding assistants like Claude, ChatGPT, and Cursor can generate working code in seconds.

"When godly intelligence is on tap and can solve any problem in three seconds, those amalgamations of systems become bottlenecks," Cooper told VentureBeat. "What was really cool for humans to deploy in 10 seconds or less is now table stakes for agents."

The company claims its platform delivers deployments in under one second — fast enough to keep pace with AI-generated code. Customers report a tenfold increase in developer velocity and up to 65 percent cost savings compared to traditional cloud providers.

These numbers come directly from enterprise clients, not internal benchmarks. Daniel Lobaton, chief technology officer at G2X, a platform serving 100,000 federal contractors, measured deployment speed improvements of seven times faster and an 87 percent cost reduction after migrating to Railway. His infrastructure bill dropped from $15,000 per month to approximately $1,000.

"The work that used to take me a week on our previous infrastructure, I can do in Railway in like a day," Lobaton said. "If I want to spin up a new service and test different architectures, it would take so long on our old setup. In Railway I can launch six services in two minutes."

Inside the controversial decision to abandon Google Cloud and build data centers from scratch

What distinguishes Railway from competitors like Render and Fly.io is the depth of its vertical integration. In 2024, the company made the unusual decision to abandon Google Cloud entirely and build its own data centers, a move that echoes the famous Alan Kay maxim: "People who are really serious about software should make their own hardware."

"We wanted to design hardware in a way where we could build a differentiated experience," Cooper said. "Having full control over the network, compute, and storage layers lets us do really fast build and deploy loops, the kind that allows us to move at 'agentic speed' while staying 100 percent the smoothest ride in town."

The approach paid dividends during recent widespread outages that affected major cloud providers — Railway remained online throughout.

This soup-to-nuts control enables pricing that undercuts the hyperscalers by roughly 50 percent and newer cloud startups by three to four times. Railway charges by the second for actual compute usage: $0.00000386 per gigabyte-second of memory, $0.00000772 per vCPU-second, and $0.00000006 per gigabyte-second of storage. There are no charges for idle virtual machines — a stark contrast to the traditional cloud model where customers pay for provisioned capacity whether they use it or not.

"The conventional wisdom is that the big guys have economies of scale to offer better pricing," Cooper noted. "But when they're charging for VMs that usually sit idle in the cloud, and we've purpose-built everything to fit much more density on these machines, you have a big opportunity."

How 30 employees built a platform generating tens of millions in annual revenue

Railway has achieved its scale with a team of just 30 employees generating tens of millions in annual revenue — a ratio of revenue per employee that would be exceptional even for established software companies. The company grew revenue 3.5 times last year and continues to expand at 15 percent month-over-month.

Cooper emphasized that the fundraise was strategic rather than necessary. "We're default alive; there's no reason for us to raise money," he said. "We raised because we see a massive opportunity to accelerate, not because we needed to survive."

The company hired its first salesperson only last year and employs just two solutions engineers. Nearly all of Railway's two million users discovered the platform through word of mouth — developers telling other developers about a tool that actually works.

"We basically did the standard engineering thing: if you build it, they will come," Cooper recalled. "And to some degree, they came."

From side projects to Fortune 500 deployments: Railway's unlikely corporate expansion

Despite its grassroots developer community, Railway has made significant inroads into large organizations. The company claims that 31 percent of Fortune 500 companies now use its platform, though deployments range from company-wide infrastructure to individual team projects.

Notable customers include Bilt, the loyalty program company; Intuit's GoCo subsidiary; TripAdvisor's Cruise Critic; and MGM Resorts. Kernel, a Y Combinator-backed startup providing AI infrastructure to over 1,000 companies, runs its entire customer-facing system on Railway for $444 per month.

"At my previous company Clever, which sold …

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🔗 Sumber: venturebeat.com