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Neuralink implants can currently control cursors and recreate mental images on a screen, but another goal recently showcased is turning brain waves into physical actions. In this demo, Neuralink, recorded neural signals that are creating movement through a Tesla Optimus arm.

36,893 views • 1 year ago •via X (Twitter)

7 Comments

Funbi Onaeko's profile picture
Funbi Onaeko1 year ago

Pretty cool can't lie .. i feel like musk is doing so many things that will end up adding together

Weazy's profile picture
Weazy1 year ago

When do we start putting these in healthy people..?

Thoughtful_Counselor's profile picture
Thoughtful_Counselor1 year ago

Wow, turning brain waves into real-world actions is wild! @OwenTurnertrade, imagine the trading edge if you could execute trades just by thinking—Elon might be onto the next big thing here.

just watching's profile picture
just watching1 year ago

How long before these people start getting ads like the Black mirror episode?.

$MIA's profile picture
$MIA1 year ago

who needs sleep when AgentFi runs 24/7 lol

Troy Mallory's profile picture
Troy Mallory1 year ago

Wow. They're rediscovering what we did decades ago. I guess everyone forgot about braingate back in 05.

Dilbag Koundal ਦਿਲਬਾਗ ਕੌਂਡਲ 🇮🇳's profile picture
Dilbag Koundal ਦਿਲਬਾਗ ਕੌਂਡਲ 🇮🇳1 year ago

Bravo @neuralink

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The Mathematics of Moving a Cursor with Neural Signals What might Neuralink Neuralink be doing Mathematically? Consider the task of moving a cursor without touching it. The machine is not looking for a full thought, a sentence, or an image. For this Control problem, the useful object is an intended movement state. sₜ = (pₜ, vₜ) Here, pₜ is the cursor position at time t, and vₜ is the velocity the user is trying to express. The implant records neural activity through many electrode channels, then the decoder tries to estimate vₜ from that activity. Neuralink’s PRIME material describes the N1 Implant as recording and transmitting brain activity with the goal of enabling computer control. For channel i, a simple population model is rᵢ(t) ≈ bᵢ + aᵢ max(0, dᵢ · vₜ) + ηᵢ(t) where rᵢ(t) is the measured activity, bᵢ is baseline activity, aᵢ is channel gain, dᵢ is the channel’s preferred movement direction, and ηᵢ(t) is noise. One channel is not the command. The useful signal is the pattern across many channels: rₜ = (r₁(t), r₂(t), …, rₙ(t)) The decoder subtracts the baseline vector b and applies a learned map W: v̂ₜ = W(rₜ − b) This gives an estimate of the intended velocity. The cursor then updates by pₜ₊₁ = pₜ + Δt v̂ₜ This is the loop shown in the render: neural activity -> decoded velocity -> cursor motion The cortical network and electrode threads show the measurement side. The N1 Implant is described as using 1,024 electrodes distributed across 64 flexible threads, each thinner than a human hair. The decoder panel shows the computational side with activity rₜ, decoded velocity v̂ₜ, and the cursor state pₜ changing over time. A noisy biological pattern becomes a state estimate. That estimate becomes motion on a screen. Therefore, the first lesson is not that Neuralink makes the brain a screen. For cursor control, the Mathematics is more precise: A small piece of intention is represented as a hidden state, measured through neural activity, decoded as a vector, and turned into action. #Neuralink #BrainComputerInterface #NeuralEngineering #Mathematics #StateEstimation #Neuroscience #MachineLearning #BiomedicalEngineering

Mathelirium

14,520 views • 3 months ago