First Place in the NLB Challenge

AE’s data science team took first place in the first Neural Latents Benchmark (NLB) challenge, topping the leaderboard in every category! We reinvested the prize money to sponsor a phase II of the NLB Challenge and have offered cloud computing grants to all participating teams.

What is BCI?

Brain Computer Interfaces (BCI) are the hardware and software that allow information to flow directly between brains and computing devices (computers, smartphones, robots, electrical simulators of limbs, etc.)

The hardware reads brain activity from electrical signals, blood flow, or other features that reflect underlying brain activity. The software then reveals patterns in those signals, interprets those patterns, and converts them into commands a computer can understand.

brain computer interface

Want to discuss BCI or simply learn more about AE?

What are we doing?

AE Studio's theory of change was to create a profitable consulting business that could generate capital to invest in startups, which would then create more capital to invest in accelerating BCI to increase human capabilities and solve AI alignment. This plan has worked better and faster than we expected.

We've made quantifiable progress in enhancing human abilities through accelerating BCI development. This has been achieved by our dedicated BCI and AGI Alignment teams, with advancements made via open-source software, expert collaborations, research initiatives, and increased community engagement.

Demonstrating our technical expertise, we won first place in the Neural Latent Benchmark Challenge, a prestigious competition in the BCI community that applies machine learning to neural signals. We have open-sourced our solution and funded the second round of the competition as a means to propel the BCI field forward.

To ensure the relevance and effectiveness of our efforts, we have established collaborations with respected experts in the BCI, neuroscience, cognitive science, and AGI sectors, including Dr. Sumner Norman, our former Chief BCI Scientist, and Prof. Michael Graziano of Princeton University, who focuses on the neurological basis of consciousness.

These collaborators complement our internal team’s skills in cognitive neuroscience, BCI, physics, pure mathematics, robotics, and computer science. The knowledge and influence contributed by our collaborations have bolstered our capacity to deliver outstanding results in the domains of AI alignment and BCI.

brain computer interface

What have we built?

We're using formal verification methods in our R&D for reliability and safety of systems we develop. This includes creating new verification methods for brain-computer and human-AGI interactions, thorough checking of our software, applying these techniques to our neuroscience research, and community collaboration for data storage and analysis procedures verification. With this approach, we have:

  • Lowered the barrier of entry to BCI entrepreneurs by releasing open-source software such as the Neurotech Development Kit

  • Accelerated the development of BCI development, by contributing to existing open-source offline neuro-analysis software and sitting on the steering council of these packages

  • Accelerated the development of real-time BCI systems by creating neural data simulators, co-created with leading BCI scientist Dr. Chadwick Boulay

  • Improved the neuroscience and BCI landscape by enabling sharing and reuse of data by developing and supporting open data standards.

We work with the community to identify neglected approaches and projects with an outsized impact that we can contribute to. Our commitment to our long-term vision and proven ability to execute technically complex projects in the BCI and AI space demonstrate our competence and dedication to making a significant and lasting positive impact on the future of humanity.

Why does this matter?

Humans have deployed technology to increase their agency since the agricultural revolution, at an accelerating pace.

Our relationship with computers has already increased human agency and transcription fluency dramatically. When computers begin responding to our thoughts directly, these effects can be accelerated…if BCI is developed with that intent. Alternatively, BCI could reduce our agency if its creators are narrowly-focused on short-term commercial incentives.

Our position: BCI should enhance the agency of its users. If you think dark patterns are bad, imagine interruption of thought with ads that sell neural data to the highest bidder without consent. If BCI is designed like modern technology, we can expect both. We want to nudge the field in the right direction.

Currently, BCI technology is being deployed to restore hearing via cochlear implants, restore use of paralyzed limbs, and to treat Parkinson’s disease.

Despite this potential, it remains a neglected topic with potential restorative and augmentative applications we cannot yet imagine. AE exists to increase human agency and ensure neuroethical principles are maintained as the journey continues.

AE creates technology for organizations, and individuals that want to maximize their agency. As we continue to grow, we will better understand and derive the neuroethical principles needed for the development of the best version of BCI for humanity.

brain computer interface
brain computer interface

How can AE help us get there?

We maintain independence and avoid shareholders, venture capital, and private equity (Google’s founders never wanted ads, but their investors did). AE is already a fully-bootstrapped business that has grown from 0 to ~150 with agency-increasing BCI as its ambitious Big, Hairy, Audacious Goal.

We are growing a profitable, longtermist software company, training the best developers, designers, and engineers on this planet (or any other), building agency-increasing products for those clients and ourselves, and investing in altruistic, agency-increasing BCI initiatives. We love funding internal skunkworks projects

We follow the core principles of increasing human agency, rather than short-term financial incentives, A/B testing baby steps, and realizing that we are only 1% as good as we could be.

What can you do?

If you are an academic researcher looking to improve your neural decoding algorithms or (re)create a real-time decoder, we’re here to help!

If you are a hardware company interested in joining a select list of early adopters using our technology for decoding brain signals using state-of-the art techniques, or want to understand how the data from your hardware can help improve human agency, come talk to us!

If you are a developer or data scientist, excited, curious, or concerned about the future of BCI, join our team!

brain computer interface