
Adaptive Security is OpenAI’s investment for AI cyber threats. The company was founded in 2024 by serial entrepreneurs Brian Long and Andrew Jones. Adaptive has raised $50M+ from investors like OpenAI, a16z and executives at Google Cloud, Fidelity, Plaid, Shopify, and other leading companies.
Adaptive protects customers from AI-powered cyber threats like deepfakes, vishing, smishing, and email spear phishing with its next-generation security awareness training and AI phishing simulation platform.
With Adaptive, security teams can prepare employees for advanced threats with incredible, highly customized training content that is personalized for employee role and access levels, features open-source intelligence about their company, and includes amazing deepfakes of their own executives.
Customers can measure the success of their training program over time with AI-powered phishing simulations. Hyper-realistic deepfake, voice, SMS, and email phishing tests assess risk levels across all threat vectors. Adaptive simulations are powered by an AI open-source intelligence engine that gives clients visibility into how their company's digital footprint can be leveraged by cybercriminals.
Today, Adaptive’s customers include leading global organizations like Figma, The Dallas Mavericks, BMC Software, and Stone Point Capital. The company has a world class NPS score of 94, among the highest in cybersecurity.
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Most AI video tools hand you a black box: closed weights, a subscription, and no way to see what is happening under the hood. LTX takes the opposite approach. Built by Lightricks, LTX is an open foundation model that generates and simulates across video, audio, and the physical world, and it puts the weights, the code, and the control in your hands.
At the center of the model is LTX-2.5, a 22B-parameter dual-stream diffusion transformer that produces native 4K video at up to 50 frames per second, with audio and video generated together in a single pass rather than stitched together afterward. Artificial Analysis, an independent benchmarking group, currently ranks LTX among the top three AI video models in the world.
You choose how you want to use it. Download the open weights and run LTX-2.5 on your own hardware. License the model for on-premise deployment backed by enterprise support. Or build directly on LTX Studio, the production suite that turns the model into a full creative workflow. Companies like ElevenLabs, Asteria Film Co., Magnopus, and NVIDIA already rely on LTX for their own work.
LTX is not built for one-off social clips. It is infrastructure for teams that generate motion, audio, and physical environments as part of their own products and pipelines.
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Nemotron 3 Ultra
Nemotron 3 Nano is a small yet powerful large language model from NVIDIA's Nemotron 3 series, specifically crafted for effective agentic reasoning, interactive dialogue, and programming assignments. Its innovative Mixture-of-Experts Mamba-Transformer framework selectively activates a limited set of parameters for each token, ensuring rapid inference times without sacrificing accuracy or reasoning capabilities. With roughly 31.6 billion parameters in total, including about 3.2 billion active ones (or 3.6 billion when factoring in embeddings), it surpasses the performance of the previous Nemotron 2 Nano model while requiring less computational effort for each forward pass. The model is equipped to manage long-context processing of up to one million tokens, which allows it to efficiently process extensive documents, complex workflows, and detailed reasoning sequences in a single cycle. Moreover, it is engineered for high-throughput, real-time performance, making it particularly adept at handling multi-turn dialogues, invoking tools, and executing agent-based workflows that involve intricate planning and reasoning tasks. This versatility positions Nemotron 3 Nano as a leading choice for applications requiring advanced cognitive capabilities.
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Apollo Autonomous Vehicle Platform
A combination of sensors, including LiDAR, cameras, and radar, gather data from the vehicle's surroundings. By employing sensor fusion technology, perception algorithms are capable of identifying, locating, measuring the speed, and determining the orientation of various objects on the road in real time. This advanced autonomous perception system is supported by Baidu's extensive big data infrastructure and deep learning capabilities, along with a rich repository of labeled real-world driving data. The robust deep-learning platform, complemented by GPU clusters, enhances processing power. Additionally, the simulation environment enables virtual driving across millions of kilometers each day, leveraging diverse real-world traffic and autonomous driving data. Through this simulation service, partners can access an extensive array of autonomous driving scenarios, allowing for rapid testing, validation, and optimization of models in a manner that prioritizes both safety and efficiency, ultimately fostering advancements in autonomous vehicle technology.
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