The performance ceiling for non-invasive Brain-Computer Interfaces (BCIs) is rising dramatically, not from better sensors, but from advanced AI. New models can extract high-fidelity signals from noisy data collected outside the skull, potentially making surgical implants like Neuralink unnecessary for sophisticated use cases.

The company's next product will provide objective brain state data, much like a CGM provides constant glucose readings. This allows for data-driven mental health treatment, moving beyond subjective checklists and enabling closed-loop therapies with neuromodulators, fundamentally changing diagnostics and care.

Dan Siroker outlines a three-part roadmap for achieving mind emulation: 1) a complete brain map (connectome), now feasible by 2040; 2) sufficient, cheap compute power, estimated to be ready by 2047; and 3) rich behavioral data, which the Limitless pendant is designed to capture.

Challenging Neuralink's implant-based BCI, Merge Labs is creating a new paradigm using molecules, proteins, and ultrasound. This less invasive approach aims for higher bandwidth by interfacing with millions of neurons, fundamentally rethinking how to connect brains to machines.

The supply chain for neurons is not the main problem; they can be produced easily. The true challenge and next major milestone is "learning in vitro"—discovering the principles to program neural networks to perform consistent, desired computations like recognizing images or executing logic.

The team obsesses over perfecting the BCI cursor, treating it as the key to user agency on a computer. However, the long-term vision is to eliminate the cursor entirely by reading user intent directly. This creates a fascinating tension of building a masterwork destined for obsolescence.

A "frontier interface" is one where the interaction model is completely unknown. Historically, from light pens to cursors to multi-touch, the physical input mechanism has dictated the entire scope of what a computer can do. Brain-computer interfaces represent the next fundamental shift, moving beyond physical manipulation.

Paradromics uses LLMs to decode brain signals for speech, much like how speech-to-text cleans up audio. This allows for faster, more accurate "thought-to-text" by predicting what a user intends to say, even with imperfect neural data, and correcting errors in real-time.

New artificial neurons operate at the same low voltage as human ones (~0.1 volts). This breakthrough eliminates the need for external power sources for prosthetics and brain interfaces, paving the way for seamless, self-powered integration of technology with the human body.