Axiomatic_AI

मुख्यालय

🇺🇸Boston, MA

उद्योग

प्रौद्योगिकी, सूचना और इंटरनेट

कर्मचारी

32

स्थापना वर्ष

2024

कंपनी का प्रकार

Privately Held

रैंकिंग

#1,51,20,853

Axiomatic_AI is readying to launch with the aim to accelerate R&D by "Automated Interpretable Reasoning" (AIR) -- a verifiably truthful AI model built for reasoning in science and engineering. Axiomatic_AI is hiring top talent interested in a future of human reasoning aided by -- not replaced by -- AI, and a future that empowers a new generation of innovators to solve important problems thro The Challenge and Opportunity: Mission 10X30 - Pioneering a Tenfold Boost in Science & Engineering Productivity by 2030 At the heart of our mission lies the ambition to create software and algorithms that not only automate processes but also provide clear, understandable insights to fuel innovation and research. Our aim? To achieve Mission10X30, a bold vision aiming for a tenfold decrease in the time engineers spend tackling technical challenges by 2030. How? Through our groundbreaking AI-engineering tool - Axiomatic AI. This tool is designed to streamline end-to-end prototype development, with a primary focus on the largest segments of semiconductor-based hardware. Background: The scientific method stands as one of humanity's most remarkable achievements, guiding us through a journey of understanding via iterative experimentation and evidence-driven deduction. In a mere fraction of Earth's history - less than 0.001% - this methodology has propelled us from the Industrial Revolution to the digital age. Now, with the emergence of artificial intelligence, we stand at a crossroads: a future where AI replaces humans, or one where AI empowers us through Automated Interpretable Reasoning. Our Unique Approach: Axiomatic AI introduces a novel methodology grounded in evidence-driven deduction, deeply rooted in the fundamentals of physics and engineering knowledge. Our goal? To showcase the practicality of axiomatic AI through demonstrative projects, starting with physics and engineering domains. Unlike conventional black-box AI, our approach offers transparency and interpretability.