Urgent.News

600+ sources. One page. See who else covered it.

Editions

AI

AI is ready to run spacecraft. Is the space industry ready for it? (op-ed)

Satellite constellations are getting bigger and increasingly difficult for human operators to manage. Artificial intelligence will soon be able to help, but will the space industry let it happen?

AI is ready to run spacecraft. Is the space industry ready for it? (op-ed)

Martin Halliwell, a Partner at NewSpace Capital and former Chief Technology Officer of SES, discusses the potential of artificial intelligence (AI) in the space industry. With over 16,000 active satellites orbiting Earth, predictions suggest this number could grow significantly in the coming years, reaching up to 70,000 low-Earth orbit (LEO) satellites in just five years.

The rapid growth of satellite constellations poses challenges for human operators, who must manage, coordinate, and ensure proper functioning of these networks. AI offers a solution to these challenges by enabling onboard processing, automation, and data analysis in orbit.

One of the primary uses for AI in orbit is to process satellite data more efficiently. Currently, most data is transmitted back to Earth for sorting and analysis, leading to increased costs and time delays. AI can analyze data in orbit and send back only relevant information, cutting costs and saving time. This capability is especially crucial in defense applications, where speed can be a decisive factor.

Additionally, AI can help satellites adapt to changing demand for bandwidth by adjusting beam directions, power levels, and capacity allocation in real-time, ensuring more efficient use of limited resources.

However, the integration of AI in the space industry is not without challenges. Legal, organizational, and cybersecurity issues must be addressed to ensure safe and responsible implementation. As AI systems take on more decision-making responsibilities, determining liability for potential errors or damages becomes increasingly complex.

Clear guidelines must be established to delineate the roles and decision-making authority between AI systems, manufacturers, operators, and software providers. Moreover, the rapid advancement of AI technology necessitates the development of robust testing, cybersecurity measures, and clear legal frameworks to foster trust and confidence in AI-driven space systems.

Written by urgent.news from Space.com's reporting — not their text. Machine-written — it may contain errors, so check the original before relying on it.

Read the original at space.com →

More in AI

Open Discovery Challenge: How to Build a Verifiable Judge for AI-Designed Malaria Drugs

Open Discovery Challenge: How to Build a Verifiable Judge for AI-Designed Malaria Drugs Generative models can propose thousands of plausible molecules in a day.

  • Open Discovery Challenge aims to create a verifiable judge for AI-designed malaria drugs
  • Successful drug must inhibit PfDHODH enzyme without affecting human counterpart
  • Scoring system validation revealed toxicity gate errors, size bias, and novelty scoring issues

Why your AI coding agent should never see your API keys

Your AI coding agent needs your API keys. It needs them to call services, to test integrations, to run your stack. So you give it .env files, or you export keys into the environment, or you paste them…

  • API keys must remain secure when using AI coding agents
  • Developers often expose keys via .env files or environment exports
  • AI agents can leak secrets through context, output echo, and prompt injection