Adaptive Security was founded in 2024 by seasoned entrepreneurs Brian Long and Andrew Jones. Since inception, the company has raised over $50 million from top-tier investors including OpenAI, Andreessen Horowitz, and executives from Google Cloud, Fidelity, Plaid, Shopify, and other industry leaders.
Adaptive defends organizations against sophisticated, AI-driven cyber threats such as deepfakes, vishing, smishing, and spear phishing. Its next-generation security awareness training and AI phishing simulation platform enables security teams to deliver ultra-personalized training that adapts to each employee’s role, access level, and exposure. This training leverages real-time open-source intelligence (OSINT) and features highly convincing deepfake content—including synthetic media of a company’s own executives—to mirror real-world attack vectors.
Through AI-powered simulations, customers can continuously assess and improve organizational resilience. Hyper-realistic phishing tests across voice, SMS, email, and video channels evaluate risk across every major vector. These simulations are fueled by Adaptive’s AI OSINT engine, giving teams deep visibility into how attackers might exploit their digital footprint.
Today, Adaptive serves global leaders like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. With an industry-leading Net Promoter Score of 94, Adaptive is redefining excellence in cybersecurity.
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RunPod offers a robust cloud infrastructure designed for effortless deployment and scalability of AI workloads utilizing GPU-powered pods. By providing a diverse selection of NVIDIA GPUs, including options like the A100 and H100, RunPod ensures that machine learning models can be trained and deployed with high performance and minimal latency. The platform prioritizes user-friendliness, enabling users to create pods within seconds and adjust their scale dynamically to align with demand. Additionally, features such as autoscaling, real-time analytics, and serverless scaling contribute to making RunPod an excellent choice for startups, academic institutions, and large enterprises that require a flexible, powerful, and cost-effective environment for AI development and inference. Furthermore, this adaptability allows users to focus on innovation rather than infrastructure management.
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DriveMod
DriveMod serves as Cyngn's all-encompassing solution for autonomous driving, effectively integrating with widely used sensing and computing technologies to enable industrial vehicles to interpret their surroundings, make sound decisions, and carry out actions. This cutting-edge system is crafted to blend seamlessly into your existing operations, facilitating easy programming of vehicle routes, loops, and missions. In essence, DriveMod is capable of performing any task that a human driver can accomplish. Additionally, you can enhance any commercially available vehicle with autonomous capabilities through a straightforward retrofit procedure. The flexibility of DriveMod ensures that various fleets can operate smoothly, irrespective of the vehicle's make or model. By harnessing advanced AI software along with high-quality sensors and computing systems, DriveMod offers a level of performance that outshines human operators. It has the ability to recognize thousands of objects and assess numerous potential routes, swiftly determining the most efficient path in mere fractions of a second, which fundamentally transforms how vehicles navigate their environment. This impressive functionality establishes DriveMod as a frontrunner in the field of autonomous vehicle solutions, paving the way for the future of transportation technology. Furthermore, the system's continuous updates and improvements ensure that it remains at the cutting edge of innovation in this rapidly evolving industry.
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NVIDIA DRIVE Map
NVIDIA DRIVE® Map is a sophisticated mapping solution specifically designed to bolster vehicle autonomy while prioritizing safety. It combines accurate ground truth mapping with the nimbleness and extensiveness of AI-powered fleet-generated mapping, yielding impressive outcomes. The platform incorporates four unique localization layers—camera, lidar, radar, and GNSS—offering essential redundancy and adaptability for advanced AI-driven systems. Emphasizing unparalleled accuracy, the ground truth map engine creates DRIVE Maps by synthesizing data from various sensors, such as cameras, radars, lidars, and differential GNSS/IMU, all collected via NVIDIA DRIVE Hyperion data collection vehicles. It achieves remarkable precision of under 5 cm, especially in high autonomy contexts (L3/L4), in settings like urban landscapes and highways. Tailored for swift performance and global compatibility, DRIVE Map takes advantage of both ground truth and fleet-generated data, representing the collective intelligence of millions of vehicles on the road. This cutting-edge methodology not only improves mapping accuracy but also plays a vital role in advancing the future of autonomous driving technology, paving the way for safer roadways and smarter transport systems.
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