ChatGPT in Space: How AI Can Transform Deep Space Missions

As we set our sights on exploring distant planets and galaxies, the role of data and technology in space missions has never been more critical. One emerging technology that holds promise for addressing some of space travel's most pressing challenges is large language models (LLMs) like ChatGPT, a state-of-the-art natural language processing AI.

Here we'll unpack the transformative potential of tools like ChatGPT in enhancing real-time communication, improving data quality, and even mitigating the psychological toll of long-haul missions. We'll also delve into the technical and ethical hurdles that need to be overcome to make AI-powered space travel a reality.

What are the Benefits of ChatGPT for Space Travel?

Using an AI to aid in space exploration may sound like a plot from a sci-fi novel, yet such a reality may not be so far off. There are several potential benefits of using tools like ChatGPT for space travel.

Bypass the communication delay

One of the major operational challenges in space travel is communication between ground-based operations teams and space-faring astronauts.

This communication has historically been conducted using radio waves, which like all bands of the electromagnetic spectrum, travel at the speed of light (670,000,000 mph).

Because of the finite speed limit of light, it takes time for the communication to pass from sender to receiver through the vacuum of space. For communication with the International Space Station (ISS) or the moon, this “delay” is small, less than three seconds, but for more distant communications, this delay creates operational challenges.

If/when humans step foot on Mars, it will take between 5-20 minutes for the ground team to receive the good news, and for more distant planets, the delay will be measured in hours.

Astronauts frequently encounter technical and operational challenges that require support from mission control, from performing maintenance and troubleshooting equipment faults to aligning on objectives in changing circumstances.

For Mars and beyond, these communications with ground control will be impractical in many situations, so astronauts will need live operational support from their remote location.

AI will open the door for a remote “operational assistant” that has knowledge of systems, equipment, and mission objectives and can be stored onboard in the spacecraft’s computer systems. Such systems will allow humans to interact with them using natural language or speech. This bypasses the need to communicate with ground control or spend time searching and digesting the information from equipment manuals.

Fix data quality issues

Astronomical data, particularly received transmissions and images, can be incredibly noisy due to various astronomical phenomena. Like how Adobe and other tech companies have developed natural language interfaces for fixing images and audio, it is entirely possible that AI can be applied to clean up this noisy astronomical data.

Combat loneliness

For missions to Mars and other long-haul space missions, the psychological impact on humans is one of the biggest concerns. How will a small group of people largely cut off from the rest of humanity and in an entirely foreign environment cope?

ChatGPT-like models could be created to specifically address this issue, almost acting as remote therapists and companions.

What are the Possible Problems of Using AI-Chat in Space?

Of course, using a tool similar to ChatGPT in space is far from a simple solution. There are several potential issues with implementing such a tool.

Natural language can be vague and nuanced

Natural language is not the most specific means of communication that humans have invented, which is why technical concepts are often expressed in the precise language of mathematical formulas or raw numbers.

Conversely, space travel must be ultra-precise to ensure that operations progress smoothly.

AI chat models designed for space flight will need to place a heavy emphasis on returning a very precise output from a potentially imprecise human input. You can learn more about natural language processing in a separate tutorial.

Data bandwidth makes updates slow or impossible

AI is a fast-paced technology, with major advancements separated by weeks or months rather than years. Additionally, AI models and the systems they are integrated into require maintenance and updates.

This fact isn’t an issue on Earth, where models live in the cloud, connected by high-speed internet, but in space, data transmission can be slow or poor quality due to bandwidth restraints, telemetry limitations (uncertainty in an object’s exact position), or other astronomical phenomena, such as gamma-ray-bursts (GRBs), solar winds, or planetary climate interference.

Lack of emotional and ethical understanding

AI and other natural language models like ChatGPT are currently poor at recognizing and processing emotions and lack the framework to make decisions that consider not only task objectives but the ethics and implications of its decisions. This could prove problematic if an astronaut relies on an AI for human-like levels of support.

How Can NASA Prevent Hallucinations and Other Problems With AI for Astronauts?

There are several ways that space agencies can address some of the current challenges with artificial intelligence, particularly that of hallucinations. When we refer to hallucinations, we mean mistakes that the LLM generates, which may appear plausible but are actually incorrect, nonsensical, or made up.

Reinforcement Learning with Human Feedback (RLHF) in simulated environments

No AI model is perfect from the off. Even ChatGPT relied on RLHF, which is a process of using humans to the quality of responses from the model and feeding it back so the model can be tweaked to produce responses more in line with the end-users expectations.

For AI in space travel, this would almost certainly come from simulated scenarios, where humans would use the AI to answer questions or solve problems and rate the quality of relevance of the response.

Follow best practices when building AI systems

AI systems should never be designed where user input is sent to a model, and the model response is simply returned to the end-user.

What if the user’s question is outside of the model’s capabilities (a frequent cause of hallucination)? What if the model’s response is too long, too short, or inaccurate?

AI systems built on large language models (LLMs), like ChatGPT, should be built as layers, where both the user’s input and the model’s output pass through multiple layers of validation and moderation to ensure that the system as a whole meets the necessary accuracy and relevance thresholds.

You can learn more about building LLM applications with Langchain in a separate tutorial.

Final Thoughts

As we venture further into the cosmos, the challenges we face grow exponentially, but so do the technological solutions at our disposal.

ChatGPT and similar AI models offer a tantalizing glimpse into a future where real-time communication, data analysis, and even emotional support can be provided, regardless of the vast distances that separate Earth from the final frontier.

While there are hurdles to overcome, including the nuances of natural language and ethical considerations, the potential benefits are too significant to ignore. As data science and AI continue to evolve, their applications in space exploration are limited only by our imagination.

If you're intrigued by the possibilities of ChatGPT and want to delve deeper into its capabilities, we highly recommend taking our Introduction to ChatGPT course. It's a fantastic starting point for anyone interested in understanding the mechanics and applications of this groundbreaking AI model.