Does Intelligence Require a Brain Like Ours?
What if the most sophisticated intelligence you encountered this week wasn’t running on a GPU cluster or trained on a trillion tokens — but was sitting quietly in a tide pool, solving problems with nine semi-autonomous brains? That question isn’t rhetorical. It’s the one I found myself asking after reading about Netflix’s new film Remarkably Bright Creatures, starring Sally Field and Lewis Pullman, which began streaming this week and is based on the New York Times bestselling novel of the same name.
I don’t typically write about film. But when a story about an octopus starts trending in the same week I’m deep in research on distributed agent architectures, I pay attention. The overlap is not superficial.
The Film, Briefly
Lewis Pullman and Sally Field lead the adaptation of Shelby Van Pelt’s novel, which has drawn strong early attention on Netflix. Pullman has noted in interviews that the book’s author imagined Sally Field specifically in the role she’s now playing — a rare case of casting that closes a loop between creative intention and final execution. The story centers on an unlikely connection between a woman grieving a loss and a remarkably perceptive giant Pacific octopus living in a local aquarium.
Screen Rant named it one of the top three films to watch on Netflix this weekend. Sentinel Colorado’s review specifically called out the octopus as a genuine presence in the film — not a gimmick, but a character with apparent interiority, problem-solving behavior, and something that reads, uncomfortably, like awareness.
That last part is where my researcher’s brain refuses to stay quiet.
Distributed Intelligence as Architecture
An octopus has a central brain, yes — but roughly two-thirds of its neurons live in its arms. Each arm can taste, touch, and react to its environment with a degree of independence from the central system. This is not metaphor. This is a working model of distributed cognition that evolution stress-tested over hundreds of millions of years.
In agent architecture research, we spend enormous effort on the question of how much autonomy to give sub-agents. How much should a peripheral node act on local information versus waiting for central coordination? How do you prevent conflicting actions when multiple agents operate in parallel? How do you maintain coherent goal-pursuit across a system where no single node holds the full picture?
The octopus solved this. Not perfectly, not with a whitepaper, but functionally — in a way that produces behavior sophisticated enough that a novelist built an entire story around it, and audiences find that story emotionally credible.
What Agent Designers Can Actually Take From This
I want to be careful here. I’m not suggesting we copy biology wholesale. Biological systems carry enormous overhead — metabolic cost, evolutionary baggage, constraints that don’t translate to silicon. But there are structural principles worth examining seriously:
- Local processing reduces latency. An octopus arm that reacts to a threat without waiting for central approval is faster and more resilient. Agent systems that push more decision-making to the node level can achieve similar gains.
- Redundancy is not waste. Distributed neural processing means no single point of failure. In multi-agent systems, this maps directly to fault tolerance and graceful degradation.
- Coherence emerges from shared goals, not constant communication. The octopus’s arms don’t check in with headquarters every 200 milliseconds. They operate within a behavioral envelope set by the central system. This is closer to how well-designed agent hierarchies should function — and often don’t.
Why a Netflix Film Is a Useful Mirror
Films like Remarkably Bright Creatures matter to researchers in a way that’s easy to dismiss and harder to defend, but I’ll try. Popular narratives about non-human intelligence shape public intuition. That intuition eventually shapes policy, funding priorities, and the questions that get asked of systems like the ones I study.
When audiences watch an octopus character and find it believable — find it sympathetic, even — they are updating their mental model of what intelligence can look like. That update is not trivial. It loosens the assumption that cognition must be centralized, language-based, or human-shaped to count as real.
Lewis Pullman and Sally Field are doing promotional work for a streaming platform. But the story they’re carrying asks a question that sits at the center of my field: how do you recognize intelligence when it doesn’t look like you?
The Question We Keep Avoiding
Agent intelligence research has a habit of building systems that mirror human cognitive architecture because that’s the architecture we understand best. We build hierarchies that look like org charts. We design reasoning chains that look like internal monologue. We evaluate outputs against human judgment.
An octopus would fail every one of those benchmarks. It would also escape your evaluation environment, solve the puzzle you didn’t know you’d set, and be gone before you finished writing up your methodology.
Maybe the most useful thing a film about a clever cephalopod can do is remind us that our benchmarks are a choice — not a law of nature.
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