# Part I. The last mechanical step | The Intent Layer Source: https://setu-labs.co/manifesto-1.html > Every computer, however capable, still waits for a human body to do something a sensor can register. That wait is now the slowest part of the system. [Download PDF ](https://setu-labs.co/assets/setu-the-intent-layer.pdf) ## The last mechanical step Every computer, however capable, still waits for a human body to do something a sensor can register. That wait is now the slowest part of the system. Somewhere tonight, a system that can draft a contract or re-plan a shipping route in seconds is doing nothing at all. It is waiting for someone to finish typing. In a hospital ward, a woman who has had a stroke knows exactly what she needs to tell the nurse. The sentence is complete. It has no way out. On a crowded train, a man has a message he would rather nobody overheard. He could say it in two seconds. He thumbs it out in forty. An idle machine, a silenced patient, a self-conscious commuter. In each case the intelligence on either side is not the limit. The channel between them is. > Computing has an input problem, and it is older than computing. #### Figure 1 (schematic): One instruction, four ways across The same intent can reach a machine by different physical routes. Each route asks something different of the body, and each stands on different evidence. Intent → Move Thursday’s review to Friday → Machine action ##### Keys and touch Mechanical input 1. Put it into words 2. Move fingers 3. Device registers contact 4. Text arrives Deployed everywhere Hands and eyes occupied. Visible to anyone watching. ##### Voice Expressive input 1. Put it into words 2. Breath, larynx, mouth 3. Sound crosses the room 4. Speech recognised Deployed widely Hands free. Audible to everyone nearby; needs a voice. ##### Silent articulation Biosignal input · peripheral, not brain 1. Put it into words 2. Mouth the words, no sound 3. Muscle or motion sensor 4. Decoder proposes text Research, early devices Private and quiet. Still a deliberate movement; accuracy is vocabulary-dependent. ##### Neural measurement Neural input 1. Attempt to speak or write 2. Cortical activity changes 3. Implant or scanner records 4. Decoder proposes text Clinical trials (implants) Wearable form Needs no working muscle. Best results today require surgery or a shielded room. ***How to read it.** Line style encodes maturity: solid = deployed at scale, dashed = demonstrated in research and early devices, dotted = demonstrated only under clinical or laboratory conditions. The moving pulse is decorative and encodes no speed data. **Sources:** Parts II–III. Schematic by the author.* ### A century of asking the body for less The history of the interface is a history of who does the translating. With punched cards, a person turned intent into holes, in advance, in the machine’s format. The command line let them type that format live. Windows replaced syntax with pointing. Touch removed the pointer. Voice removed the screen. Language models removed the last of the machine’s grammar: you can now say what you want in your own words and be understood. Step by step, translation moved from the human to the machine. Transmission did not move at all. Every one of those interfaces still needs a hand that travels or a voice that carries. #### Figure 2 (timeline): What the human had to do Each interface era cut the translation a person must perform. None, so far, has removed the need for an observable physical act. 1. 1890s ##### Punched cards Encode the request as holes, ahead of time. The machine’s format, the human’s labour. Visible act 2. 1960s ##### Command line Type exact syntax, live. Dialogue begins, in the machine’s language. Visible act 3. 1968–84 ##### Mouse and windows Point at a picture of the thing. Recognition replaces recall. Visible act 4. 2007 ##### Multi-touch Touch the thing itself. The computer goes everywhere the hand goes. Visible act 5. 2011 ##### Voice assistants Say a short command aloud. Hands freed; privacy lost. Audible act 6. 2022 ##### Language models and agents Describe the goal in your own words. The machine finally learns our language. Visible or audible act 7. Proposed ##### Biosignal and neural input Intend it deliberately; the body barely moves, or does not. Not shipped at scale. Evidence in Part II. Unobserved act · proposed ***Notes.** Dates mark when each mode became widely demonstrated or adopted (tabulating cards for census work, 1890; Engelbart’s mouse demonstration, 1968, and mass-market graphical interfaces, 1984; capacitive multi-touch phones, 2007; mainstream phone voice assistants, 2011; public chat interfaces to large language models, 2022). The final column is a proposal, not a product category.* [Image: A nineteenth-century Hollerith punched card with a grid of numbered positions and punched holes.] 1890 · Punched card [Image: A wooden box with one button and a cord: a replica of the first computer mouse.] 1964 · The first mouse (replica) [Image: A Xerox Alto computer with a portrait-orientation screen, keyboard and mouse.] 1973 · Windows and a pointer *Three objects that changed what a person had to do to be understood by a machine. Photographs via Wikimedia Commons: [Unknown author, public domain](https://commons.wikimedia.org/wiki/File:Hollerith_Punched_Card.jpg); [The wub, CC BY-SA 4.0](https://commons.wikimedia.org/wiki/File:Replica_of_prototype_Engelbart_mouse,_circa_1964,_Computer_History_Museum.jpg); [The wub, CC BY-SA 4.0](https://commons.wikimedia.org/wiki/File:Xerox_Alto_I,_1973,_Computer_History_Museum.jpg).* ### The expression ladder Sort inputs by what they ask of the body and four rungs appear. 1. **Mechanical.** You act on an object: a key, a mouse, a pane of glass. 2. **Expressive.** You act as you would toward a person: speech, gesture, gaze. 3. **Biosignal.** A sensor picks up the body preparing an act, such as a muscle firing, without the act being seen or heard. 4. **Neural.** An instrument measures the brain itself. This is a brain–computer interface, or BCI. Each rung asks less of the body and is harder to make reliable. Rung three is not rung four. A sensor on the jaw reads muscle. It does not read mind. Why climb? Because for some people the mechanical step is a wall: paralysis and stroke can leave language intact and its exits closed. Because speech is a broadcast, and much of what people want to tell a computer is not for the room. Because hands are often full. And because once software can act for us, the instructions and corrections we give it become the most valuable input in the system. ### The ChatGPT moment for BCI Not long ago, most researchers avoided the phrase “general intelligence” in print. It was a taboo. It now appears in corporate mission statements, and the world was wrong. It was wrong in a particular way. In 2017 a paper introduced the architecture every large language model now uses, and almost nobody outside the field noticed. For five years the capability compounded in plain sight. Then a text box put it in front of the public, and the consensus about what machines could do collapsed in a season. > We think BCI today is where AI was in 2017. Set the two histories side by side. In 2012 deep networks suddenly worked; in 2021 a paralysed man typed from his motor cortex. In 2017 an architecture arrived that could scale; today the first general models for brain data are being trained. In AI, the first large models and the first interface anyone could use followed within five years. We expect the same order here, at a similar pace. BCI is a few years from its ChatGPT moment: the day a device with no surgery does something useful enough that millions of people put it on. Most people are underestimating that day for the same reasons they underestimated AI.