🤖 AI Insights from the Brains at SpaceNews 🧠

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Hello, Brainiacs of the Final Frontier!

Welcome back, Meat Computers—and other Embodied Cognitions! We’re here to bring you the latest on AI’s cosmic impact—no chaos magic required.

Quick shoutout: Our subscriber base is growing faster than Agatha AI can spot a satellite maneuver. If you haven’t officially opted in yet, now’s the time to join before this newsletter goes exclusive. Don’t miss out—Sign up today!

Onward and upward,
— Brian Berger, SpaceNews Editor-in-Chief

Agatha All Along: Slingshot’s AI model part of SpaceNews Icon shortlist recognition

Slingshot Aerospace has been shortlisted for the Space News Icon 2024 award in Space Safety and Security for its innovative contributions to space situational awareness, including its advanced Agatha AI system. Agatha uses advanced AI to:

• Monitor behaviors across thousands of satellites.
• Detect potential threats and flag suspicious activities with precision.

As massive constellations continue to expand, Slingshot’s tools are redefining how we monitor and secure space.

Tech Highlights:

• AI Technique: Inverse reinforcement learning (IRL) enables Agatha to interpret satellite behaviors and determine potential intentions behind movements or maneuvers.
• Collaborative Development: Created as part of Slingshot’s PRECOG program, initiated in March 2023 and completed with results delivered to DARPA in January 2024.

Purpose: Designed for vigilant monitoring, Agatha detects everything from malfunctioning satellites to ‘wolves in sheep’s clothing’ in orbit.

While Agatha is one aspect of Slingshot’s broader space safety and security solutions, the company’s recognition as a finalist underscores the growing importance of innovative AI in safeguarding space.

DON'T FORGET: The SpaceNews Awards are happening in D.C. on Friday, Dec. 6. Seats are limited. We'd love to see you there! The after-party alone is worth the price of admission. Reserve your spot here.

AI Power Duo? Clarifai and Crimson Phoenix team up on satellite data

Last month, Clarifai and Crimson Phoenix announced a partnership to integrate their AI-enabled data labeling and computer vision expertise for enhanced real-time analysis across defense and intelligence agencies, including the U.S. Army and NGA. This collaboration addresses a sector-wide demand for rapid, automated processing of unstructured data — such as satellite images and video feeds — to support mission-critical operations.

The timing aligns closely with the recent closing of NGA’s Sequoia contract tender — a major data labeling initiative valued at over $700 million.

While Clarifai and Crimson Phoenix haven’t confirmed any direct link, the partnership clearly positions them to pursue opportunities like Sequoia. Their solution promises automation and accuracy improvements that could advance tasks such as:

• Target identification
• Equipment tracking
• Activity detection

With AI-driven insights now essential in defense, this partnership exemplifies private sector innovation supporting public sector needs — particularly where swift, precise analysis can directly impact mission outcomes.

Buzzword Watch: Inverse Reinforcement Learning (IRL)

What it is:
Inverse reinforcement learning (IRL) is an AI technique that goes beyond tracking actions to understanding motivations. It enables AI to observe behaviors and infer underlying goals—offering insight into not just what happened, but why. 

Earthly analogies:

• 🌊 Submarine Maneuvers: Think of Cold War submarine cat-and-mouse games. Submarines would go “silent” to mask their presence, follow shipping lanes to blend in, or perform diversions to throw off trackers. Their captains didn’t just monitor positions—they read intentions. By interpreting rival maneuvers, they could uncover hidden objectives, whether reconnaissance, stealth, or—heaven forbid—a preemptive strike.
  
  

• 🏈 Quarterback Reads: Similarly, elite NFL quarterbacks run rapid progressions, reading defensive formations in milliseconds to anticipate coverage schemes, disguised blitzes, and openings. Just as they interpret defensive moves to gain an edge, IRL enables AI to analyze satellite movements to see if they align with typical patterns or hint at something strategic. 

What’s good for taking a gander is also good for goosing your adversary. While IRL helps AI divine motives behind mysterious maneuvers, the same insights could help satellites blend into expected patterns, masking true intentions by learning to “fly casual.” 🛰️

Bottom line:
Inverse reinforcement learning may sound complex, but it’s fast becoming essential for interpreting—and sometimes concealing—satellite behavior in orbits where every move could tell a story.

It’s a reminder, too, of why AI feels like an arms race: for every maneuver, there’s an equal and opposite countermove, keeping everyone on their toes. 🎯

🧙🏻‍♂️SpaceNext AI Mailbag  

Q: Hi, I’ve just read the Oct. 10 newsletter. What interests me is whether we’re playing the sorcerer’s apprentice with entities such as AI without having enough hindsight on the matter. My question is, isn’t this a frantic race to win the golden ball? I mean, isn’t playing the sorcerer’s apprentice without knowing the purpose—or rather, one of the purposes—playing with fire? How can you say that this is and will remain risk-free, even if there is no such thing as ZERO risk? Shouldn’t there be a conference to ask the public what they think and take their views into consideration?
— Oliv∆res Skyblue

A: Many share your mix of wonder and caution about AI. As you put it, it can feel like we’re playing the sorcerer’s apprentice—pushing technology forward without fully understanding the consequences.

That brings to mind not only Goethe’s original tale from 1797 but also Disney’s Fantasia, where Mickey, using magic to lighten his load, finds himself overwhelmed by an army of mops and buckets flooding the room. 

Goethe wrote The Sorcerer’s Apprentice during a time of transformative inventions like the Spinning Jenny and steam engine, which were fomenting the Industrial Revolution and raising questions about human labor. Both then and now, people worry about unleashing powers without knowing where they may lead.

Today, AI brings similar risks and rewards. No path is entirely risk-free, but managing and mitigating risks is possible. For example, agencies and organizations working with space-based AI are developing standards, ethical frameworks, and cross-border collaborations to promote responsible development.

The idea of a public conference on these issues is especially compelling. Public voices remind decision-makers of broader values and concerns, which can get lost in the rush to innovate. There have been efforts to foster public dialogue on AI ethics, and perhaps it’s time for large-scale conversations within the space sector specifically.

In the end, will that be enough to save us from Skynet?—Perchance.

Until next time,
Brian 🤖🧠

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What's New With SpaceNews?

Check out the latest episode of Commercial Space Transformers, our new video series featuring conversations between SpaceNews Senior Staff Writer Jason Rainbow and the people driving the space industry’s commercial transformation. This week, SES CEO Adel Al-Saleh dives into the fleet operator’s bold moves in satellite innovation, including the Intelsat acquisition and the company’s multi-orbit strategy to outpace rivals like Starlink.

Watch out for new episodes every Tuesday on SpaceNews.com and on the SpaceNews YouTube channel.

About SpaceNext AI

SpaceNext AI is a weekly newsletter on how artificial intelligence is reshaping the space industry, delivering sharp, insightful updates on AI's role in space exploration and technology.

How We Use AI
AI assists with research and drafting, but each insight is carefully reviewed and refined by me to keep our content accurate, engaging, and relevant.

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