Namaste Yogis. Welcome to the Blockchain & AI Forum, where your technology questions are answered, mostly correct! Here no question is too mundane. As a bonus, a proverb is also included. Today’s question comes from in Mark, Naperville, USA. Mark wants to know, what is the Paul Allen Institute for Artificial Intelligence?
Mark, you came to the right place. Let’s take a moment first to understand, who was Paul Allen. Mr. Allen made his fortune as a Microsoft co-founder. Perhaps his name sounds familiar from the Microsoft connection? Allen passed away in 2018 at age 65. Too young! Lol! Before Allen’s passing, he established three research institutions, including the AI research.
Paul Allen AI Institute, commonly known as AI2, was established in 2014. AI2 is in Seattle and Tel Aviv, Israel. The mission of AI2 is “…to contribute to humanity through high impact AI research and engineering.” Let’s dive into what AI2 produces–it generates plenty—beginning with Aristo.
Aristo. Aristo was AI2’s first project. The concept powering Aristo was to create a “Digital Aristotle” capable of answering users’ questions, and ultimately holding a discussion. Aristo was designed to understand elementary science by reading relevant text. In 2019 Aristo scored over 90% on a collection of multiple-choice, eight grade science exams. Better than me, lol! AI2 readily admits Aristo remains incapable of understanding science in a meaning way. Holy ancient Greek, Batman!
Semantic Scholars. Semantic Scholar accelerates scientific breakthroughs by helping scholars locate and understand key research results, make important connections, and overcome information overload. AI2 says Semantic Scholar is an AI-based search engine for scientific literature, including more than 200 million papers covering all scientific disciplines. It draws 10M users monthly. Semantic Scholar can decode PDF files to extract and understand the full-text content beyond titles, authors, and references to include figures and concepts. Semantic Scholar played a leading role in creating the Covid-19 open research dataset.
AllenNLP. AllenNLP executes groundbreaking research in natural language processing, including improving systems’ performance, accountability, and advancing scientific methodologies for evaluating and understanding systems.
PRIOR. PRIOR is the computer vision research team. The goal is advanced computer vision leading to AI systems that can perceive the world, reason about it, and act within it. PRIOR has three research priorities: 1) embodied AI systems capable of interacting with objects, humans, and other agents in the real world; 2) vision and language multi-modal systems that can perform tasks that require an understanding of visual and language data; and 3) computer vision for the common good, e.g., a platform that can detect illegal fishing vessels via satellite imagery.
Green AI. Green AI is dedicated to reducing the cost of training and using AI systems—less expensive AI systems are accessible to more practitioners and contribute less to climate change.
Mosaic. Mosaic was formed in 2018 with the goal of building AI with common sense. Common sense is the ability to acquire and use every day experiential knowledge. Obviously, Ais lack commonsense. Good luck with this one. Lol.
AI Environment. Applied AI for climate modeling and wildlife protection.
• Earth Ranger: Software that aids ecologists and wildlife biologists make more informed wildlife conservation decisions.
• Skylight: Helps reduce illegal, unreported, and unregulated fishing through technology that provides actionable intelligence for maritime enforcement.
• Climate Modeling: The goal is to improve the world’s understanding of climate change, its effects, and what can be done now.
• Wildlands: Machine learning to support wildland fire management.
We conclude with a Norwegian proverb: Behind the clouds, the sky is always blue.
Until next time,
Yogi Nelson
Blockchain & AI Forum 