Brain-Computer Interfaces, Notes on China, Agents Infrastructure and The Bootstrapped vs. VC-Backed Math

There is no later.

Good morning

In today's edition, among other things:

• Brain-Computer Interfaces

• Notes on China

• How much does it cost to raise a round of funding?

• Anatomy of an Al o1 Prompt

• Al Agents Infrastructure Stack

• The Bootstrapped vs. VC-Backed Math

• The Complete Guide to SaaS Pricing Strategy

• The VC Fundraising Cheat Sheet: What Founders Need to Know

Onwards!

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Brain-Computer Interfaces

The human brain remains our last great frontier. We may be closer to sending humans to Mars or achieving AGI than fully understanding what happens inside our own minds. With 86 billion neurons, the brain remains the most complex natural system known to us, but it didn’t stop us from dreaming about connecting brains with computers. Let’s dive deeper.

Via byfounders:

What are Brain-Computer Interfaces (BCIs)?

Brain-computer interfaces (BCIs), also known as Brain-machine interfaces (BMI), are systems that enable direct communication between the brain and external devices, bypassing traditional pathways like muscles or speech. They work by interpreting neural signals and translating them into actionable commands for computers, prosthetics, or other machines. These technologies are no longer a distant dream—they are already helping people regain mobility, communicate, and interact with the world in ways that were unimaginable just decades ago.

There are three categories of BCIs:

• Output BCIs: Transferring information from brain activity to a device (e.g., controlling a prosthetic device).

• Input BCIs: Sending information from an external source, like a computer or sensor, directly to the brain.‍

• Closed loop BCIs: A combination of input and output capabilities. For example, decoding brain activity and then using the data to inform what “information” to send back to the brain.

How does a BCI work:

Modern BCIs function through a sophisticated three-stage process. First, specialized sensors detect electrical, magnetic, or metabolic activity across brain regions. This raw neural data then undergoes extensive processing using advanced signal analysis techniques to filter noise and identify meaningful patterns. Finally, these processed signals are translated through increasingly sophisticated algorithms into commands that control prosthetics, communication systems, or other external devices.

The BCI landscape divides fundamentally along invasiveness lines, with significant tradeoffs between signal quality and intervention risk.

Surgically-Implanted Neural Interfaces require placing electrode arrays in direct contact with brain tissue (like Neuralink).

• How they work: Electrode arrays surgically placed on or within brain tissue capture detailed neural activity from specific cell populations.

• Key players: Companies like Neuralink are developing high-density implantable threads, while Blackrock Neurotech's Utah Array has been clinically used for years.

• Advantages: Exceptional signal quality with single-neuron resolution enables precise control of external devices.

• Limitations:

  • Surgical risks, including infection and tissue damage

  • Long-term stability challenges as implants trigger immune responses

  • Eventual signal degradation through scarring or electrode shifting

  • High costs and regulatory hurdles limiting access

Wearable Neural Interfaces offer a non-surgical alternative using sensors that monitor brain activity externally. Technologies range from the well-established electroencephalography (EEG) to more advanced options like functional near-infrared spectroscopy (fNIRS) and magnetoencephalography (MEG) - (OpenBCI for example).

• How they work: External sensors detect brain activity through the skull using various technologies (EEG, MEG, fNIRS).

• Key players: Companies like Emotiv, Kernel, and OpenBCI offer headsets for research and consumer applications.

• Advantages:

  • No surgical risks

  • Broader accessibility for non-medical applications

  • Lower regulatory barriers enabling faster innovation

• Limitations:

  • Significantly lower signal quality and precision

  • Susceptibility to movement artifacts and environmental interference

  • Limited ability to target specific brain regions

Current applications are pretty mind-blowing:

Restoring Function

• Speech synthesis systems decode neural patterns from people who cannot speak, creating synthetic voices that reflect their thoughts at increasingly conversational speeds.

• Neural prosthetics allow paralyzed individuals to control robotic limbs with enough precision to perform daily tasks—from picking up cups to typing.

• Sensory restoration technologies deliver visual information directly to the brain's processing centers, bypassing damaged eyes to create functional perception patterns.

Treating Neurological Conditions

• Closed-loop stimulation systems for epilepsy detect oncoming seizures and deliver precisely timed electrical pulses to prevent them, reducing seizure frequency by up to 70% in responsive patients.

• Neural monitoring devices track brain activity patterns associated with depression, potentially offering objective biomarkers for treatment selection and response in an area traditionally reliant on subjective assessments.

• Movement disorder treatments use targeted stimulation to reduce tremors and motor symptoms in conditions like Parkinson's disease, offering better symptom control with fewer medication side effects.

Not without challenges:

But already, a lot of companies are taking on that bold vision of creating BCIs:

AI, materials science, and medicine are at the intersection of the most ambitious technological frontier.

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Notes on China

A must-see to understand current China: