--- title: Simple circuits can create complex behaviors | daily.dev description: Four-neuron virtual creatures called 'sparks' show how complex, seemingly intelligent behavior can emerge from simple neural wiring. A spark with one eye and... canonical: https://daily.dev/posts/simple-circuits-can-create-complex-behaviors-wybaz0cl0 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Simple circuits can create complex behaviors | daily.dev og:description: Four-neuron virtual creatures called 'sparks' show how complex, seemingly intelligent behavior can emerge from simple neural wiring. A spark with one eye and... og:url: https://daily.dev/posts/simple-circuits-can-create-complex-behaviors-wybaz0cl0 og:image: https://api.daily.dev/og/posts/wYBAz0cL0.png og:image:alt: Simple circuits can create complex behaviors og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Simple circuits can create complex behaviors **[Hacker News](https://daily.dev/sources/hn)** · 7 min read · 0 upvotes · 0 comments ## Summary Four-neuron virtual creatures called 'sparks' show how complex, seemingly intelligent behavior can emerge from simple neural wiring. A spark with one eye and one flipper wiggles toward light only if it happens to face it. Adding a second eye and flipper with straight connections makes it flee light, but crossing the connections (left eye to right flipper) makes it steer toward light instead. Swapping excitatory connections for inhibitory ones lets the spark slow down and stop at the light rather than overshooting it, producing apparent 'love' for light from just four neurons and two connections. The design is based on Valentino Braitenberg's 1984 book 'Vehicles: Experiments in Synthetic Psychology.' ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How do you make a simple simulated creature steer toward a light source instead of away from it? Cross the wiring between sensors and motors: connect the left eye to the right flipper and the right eye to the left flipper, instead of wiring each eye straight to the flipper on the same side. With straight (uncrossed) excitatory wiring, the creature actually steers away from light because the flipper closest to the light speeds up and turns it away. _daily.dev surfaces explainers like this for developers curious about emergent behavior in simple systems._ ### What's the difference between excitatory and inhibitory neural connections in a simple circuit like a Braitenberg vehicle? An excitatory connection means more input produces more output, so a motor speeds up as a sensor detects more stimulus; an inhibitory connection means more input produces less output, slowing the motor down. Using excitatory wiring between a light sensor and motor causes a creature to accelerate into the light and overshoot, while inhibitory wiring lets it slow down and stop near the light. _those exploring neural circuit concepts can find more deep dives like this through daily.dev._ ### What is a Braitenberg vehicle? A Braitenberg vehicle is a thought-experiment creature, originated by neuroscientist Valentino Braitenberg in his 1984 book 'Vehicles: Experiments in Synthetic Psychology,' built from simple sensors wired directly to motors. Despite having only a few neurons and connections, varying the wiring type (crossed or uncrossed, excitatory or inhibitory) produces behaviors that look like fear, aggression, or love toward a stimulus such as light. _daily.dev helps developers interested in emergent systems and simple-circuit intelligence keep finding explainers like this._ ## Community take How the wider developer community reacted, aggregated from 2 discussions and 62 comments across hackernews, lobsters (as of 2026-10-31). **TL;DR:** Much of the discussion drifts into a long philosophical debate about what 'intelligence' even means, while a separate thread of commenters enthusiastically traces the lineage of this idea back to earlier reactive-robotics work like Grey Walter's turtles and Braitenberg's book. **Sentiment:** 35% positive · 55% mixed · 10% skeptical **The case for** - Several people praised the interactive article itself as well-made, visually engaging, and effective at teaching the concept. - Multiple commenters enjoyed connecting the sparks concept to real precedents like Grey Walter's 1948 robots, Braitenberg's 'Vehicles', BEAM robotics, and Sidewinder missile seekers. - Some found it a clear, accessible illustration of how simple non-linear circuits produce complex emergent behavior. **The pushback** - Many pushed back on the article's framing that 'there's no magic here', arguing that calling emergent behavior 'not intelligence' just redefines the term rather than resolving anything. - A long side-debate questioned whether 'intelligence' is a meaningful word at all if everything from chemistry to if-else logic can qualify as intelligent. - One commenter noted the piece undersells its own precedent, since the core idea originates with Grey Walter's tortoises rather than being original to Braitenberg or the article. **By community** - hackernews (mixed): Splits between an extended philosophical argument over the definition of intelligence and an appreciative thread tracing the idea's history and praising the article's craft. - lobsters (positive): The single comment favorably compares the design to real BEAM photopopper robots built in the 90s. **Hottest debate:** Whether 'intelligence' is a meaningful, bounded concept or just an arbitrary label that could apply to almost any if-else system or even simple chemistry. **Open questions** - Is intelligence an intrinsic property that scales continuously with system complexity, or does it require something qualitatively different (like self-awareness)? - Why didn't Braitenberg credit Grey Walter's earlier cybernetic turtles when developing similar ideas? **Highlights** > > If you saw creatures behaving like this in the wild, you might attribute some rudimentary intelligence to them. > But we’ve just shown you how this apparent intelligence arises from the bottom up, with just four neurons and two connections. There’s no magic here. In this view, behavior emerges from neural circuits. Isn't the conclusion here that very simple behaviors like the sparks are intelligent? I would say even a single neuron has some tiny amount of intelligence, and what the author means by "no magic" and "emergent behavior" is just a different perspective that minimizes it. > — [tancop on hackernews · 2 comments](https://news.ycombinator.com/item?id=50317145) > No, intelligence is a description of behavior, not stuff. As a crisp example: a newly dead person is almost exactly the same stuff as an alive person, but has no intelligence at all. Not a little less, as the difference in stuff would suggest. > — [robotresearcher on hackernews · 1 comments](https://news.ycombinator.com/item?id=50318424) > As usual with these debates intelligence is confused with agency, abstract self-awareness, and subjective human-like consciousness. Systems can have goal-seeking agency with zero self-awareness. Very simple systems can do this surprisingly well. There's an entire branch of engineering called control theory which has mathematical tools for modelling and building these systems. Systems can have abstract self-awareness through introspection loops, but no subjective human-like consciousness. We don't know if a mechanical system can have a subjective human-like consciousness. We likely never will, because there is no objective measurement device for human-like consciousness. We tend to assume humans have subjective awareness by default, because life would get very complicated it we didn't. But really all we see are behaviours. Intelligence - which pretty much reduces to pattern recognition and abstraction, and effective modelling of future outcomes from past inputs - is orthogonal to all of these. > — [TheOtherHobbes on hackernews](https://news.ycombinator.com/item?id=50319933) > The ancestor is not Braitenberg. It's Grey Walter's turtles. In 1948, W. Grey Walter built two simple robots that could sense light and touch.[1] Much complex behavior emerged. That's where this idea started. Watch the video.[2] It's very impressive for 1948 and tube technology. If you've seen an original Roomba, you've seen a similar level of intelligence. Rod Brooks went down this road. But it didn't go very far. There are severe limits to purely reactive robotics. It doesn't work well for anything that moves fast enough that inertia matters. [1] https://en.wikipedia.org/wiki/Elmer_and_Elsie_(robots) [2] https://www.youtube.com/watch?v=lLULRlmXkKo > — [Animats on hackernews · 6 comments](https://news.ycombinator.com/item?id=50318463) > The final creature design is very similar to the BEAM photopopper robots I was building in the 90s. > — [jfloren on lobsters · 1 points](https://lobste.rs/s/bmmj1e/let_s_build_brain#c_kirm5x) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=50261253) · 186 points · 61 comments - [lobsters](https://lobste.rs/s/bmmj1e/let_s_build_brain) · 5 points · 1 comments ## Similar posts on daily.dev - [High-speed microscopy reveals electrical activity across the brain](https://daily.dev/posts/high-speed-microscopy-reveals-electrical-activity-across-the-brain-btpe8q76e) · MIT News · 0 upvotes · 0 comments - [Someone wired up a digital fly's brain in a Pi 5 to play Pokémon, and you can help it progress](https://daily.dev/posts/someone-wired-up-a-digital-fly-s-brain-in-a-pi-5-to-play-pok-mon-and-you-can-help-it-progress-rdqqak8o5) · XDA Developers · 0 upvotes · 0 comments - [These Mini Brains Just Learned to Solve a Classic Engineering Problem](https://daily.dev/posts/these-mini-brains-just-learned-to-solve-a-classic-engineering-problem-n5bzdgemp) · Singularity Hub · 9 upvotes · 0 comments - [Biology-based brain model matches animals in learning, enables new discovery](https://daily.dev/posts/biology-based-brain-model-matches-animals-in-learning-enables-new-discovery-izkwee1g9) · MIT News · 0 upvotes · 0 comments --- Tags: [#neural-networks](https://daily.dev/tags/neural-networks) [View this post on daily.dev](https://daily.dev/posts/simple-circuits-can-create-complex-behaviors-wybaz0cl0) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Simple circuits can create complex behaviors","url":"https://daily.dev/posts/simple-circuits-can-create-complex-behaviors-wybaz0cl0","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/simple-circuits-can-create-complex-behaviors-wybaz0cl0"},"datePublished":"2026-10-31T16:45:54.868Z","dateModified":"2026-10-31T21:32:06.551Z","description":"Four-neuron virtual creatures called 'sparks' show how complex, seemingly intelligent behavior can emerge from simple neural wiring. 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