At PL R&D, we focus on fields that have the potential to unlock transformative new capabilities for humanity. The PL Neuro Focus Area aims to accelerate breakthroughs within the fields of Neuroscience & Neurotechnology.
+ +Advances in neuroscience, brain-computer interfaces (BCIs), biologically inspired AI, and whole-brain emulation are accelerating rapidly. Together, they unlock a future where we can better understand intelligence, restore and expand human capabilities, and build entirely new forms of human-machine interaction. However, the field today remains fragmented: key technical, regulatory, infrastructure, and capital bottlenecks continue to slow progress. We aim to change that.
+ +PL Neuro exists to break bottlenecks: to define the milestones neurotech and NeuroAI need, drive the research that shifts what's believed possible, and route talent and capital to some of humanity's hardest and most important problems.
+ +We focus on three opportunity spaces that could reshape both neuroscience and computing over the coming decade:
+ +Together, these areas form a loop: advances in neuroscience (via augmentation and mapping) generate new data and understanding; those insights enable more capable AI systems and neurotechnologies (NeuroAI applications); and progress across both creates entirely new possibilities for augmenting human cognition (improved augmentation & emulation).
+ +
Neural augmentation focuses on building high-bandwidth, bidirectional interfaces between brains and computers.
+ +Near-term applications are therapeutic: restoring communication, movement, and independence for people living with paralysis or neurological conditions. Longer-term, these same technologies may enable entirely new forms of interaction, communication, and cognition that extend human capability.
+ +BCIs have already demonstrated life-changing benefits in clinical settings. The next challenge is moving from isolated medical devices to scalable platforms that support broad access and innovation.
+ +Key areas of interest include:
+ +Making neural interfaces useful beyond a small number of research participants requires progress on several fronts: how much information they can carry, how invasively they interact with neural tissue, and how they reach patients through clinical care. Recent developments show movement on each, although the devices are at different stages of clinical and commercial development.
+ +Clinical BCI Superpower
+ +Brain computer interfaces will demonstrate major improvements to the quality of life and capabilities of clinical patients - some of which will exceed the capabilities of healthy individuals - creating demand for BCIs beyond clinical applications to access these superpowers. This demand helps reach a major inflection point for BCI access and utility: 10,000 high-bandwidth neural implants in humans.
+ +The BCI App Store
+ +We believe a major catalyst will occur when BCIs transition from vertically integrated medical products into open platforms. A standardized software layer that allows third-party developers to build applications on top of approved BCI hardware could dramatically increase the utility of neural interfaces. Just as smartphones became more valuable through app ecosystems, BCIs could unlock a wave of innovation once many developers can deploy neural augmentations through scalable software deployments.
+ +
NeuroAI seeks to use insights from biological intelligence to build more capable, efficient, and accessible AI systems.
+ +Rather than treating the brain as merely an object of study, NeuroAI treats it as a source of architectural, representational, and algorithmic inspiration. NeuroAI harnesses AI tools like large-scale data collection, simulation, benchmarking, and predictive models to better understand the brain and how it operates so efficiently.
+ +Modern AI carries enormous computational and energy cost.
+ +Brains demonstrate that intelligence can emerge from systems that are dramatically more efficient than today's machine learning architectures. Understanding how biological intelligence works may help unlock and align the next generation of AI.
+ +Areas we find particularly promising include:
+ +Using neuroscience to improve AI depends on data that connects neural structure to function, and models that can extract useful patterns from those observations. Recent work is making both more accessible to researchers, with shared datasets and predictive models that allow theories of biological computation to be tested at larger scales.
+ +Neural Distillation
+ +One potential breakthrough is the emergence of methods that directly align AI systems with human neural activity. If neural recordings can help models learn more efficiently, or think in ways that better reflect human cognition, neural data could become a foundational resource for AI development. A specific inflection point would be 100,000,000 hours of human neural data recorded across cognitive tasks and recording device types.
+ +The Neuromorphic Energy Pivot
+ +A second possibility is that energy constraints push the AI industry toward biologically inspired hardware and algorithms. If brain-inspired systems achieve orders-of-magnitude improvements in efficiency vs current hardware or software designs, neuroscience could become a core driver of future AI progress.
+ +
Whole organism emulation (also known as Whole Brain Emulation (WBE)) seeks to create computational models that reproduce the behavior of biological organisms using detailed neural and biological data.
+ +While often discussed as science fiction, the field is increasingly becoming an engineering challenge shaped by advances in connectomics, imaging, simulation, and neuroscience.
+ +A successful emulation system would provide an unprecedented tool for understanding intelligence, learning, memory, and behavior.
+ +It could also dramatically accelerate neuroscience by enabling experiments that are difficult (or impossible) to perform in living systems.
+ +Promising areas include:
+ +Three major constraints sit between a fixed brain and a running simulation: how much tissue can be imaged, how much human labor reconstruction takes, and whether structural data is sufficient to specify function. Significant progress has been made against all three constraints in the past year.
+ +Memory Retrieval in Simulation
+ +The most catalytic milestone may be surprisingly simple.
+ +If a reconstructed brain or organoid can be simulated and reliably reproduce a specific learned behavior or memory from its biological counterpart in a virtual environment, whole-brain emulation moves from speculation to demonstration. Such a result would establish a concrete benchmark for the field and fundamentally change how researchers, funders, and policymakers view the possibility and impact of emulation.
+ +Mouse Brain Connectome
+ +Mapping and emulating a whole mouse connectome would be a crucial stepping stone to understanding how mammalian brains process information, and how physical connections and synapses translate into real-time brain activity, perception, and behavior. It would also provide a platform for studying mammalian synaptic plasticity—how experience changes the strength and organization of connections between neurons—and how these changes enable learning. Finally, an effort at this scale would also solidify methods and drive cost-curve improvements to make human-brain mapping feasible.
+ +Breakthroughs do not emerge from technology alone. They require healthy ecosystems that connect research institutions, domain experts, capital allocators, startup founders, and more.
+ +Today, neurotechnology faces fragmentation across disciplines, institutions, and stakeholder groups. Researchers, founders, funders, policymakers, and engineers often operate in separate communities despite working toward related goals.
+ +Building the field itself is therefore a critical leverage point. Our field-building strategy centers on:
+ +A stronger ecosystem increases the likelihood that advances in BCI, NeuroAI, and emulation reinforce one another rather than developing in isolation.
+ +The coming decade could determine whether neurotechnology remains a niche scientific endeavor or becomes one of the defining technological frontiers of the century. We believe the field is approaching several important inflection points:
+ +Reaching them will require coordinated effort across research, entrepreneurship, policy, infrastructure, and capital. PL R&D exists to help accelerate that coordination.
+ +We're actively building relationships with researchers, founders, funders, policymakers, and technologists working across neurotechnology, NeuroAI, connectomics, and related fields. You can see our latest work (including roadmaps, podcasts, and more) at plneuro.xyz.
+ +If you're interested in contributing to the future of neurotechnology or would like to attend a future PL Neuro event, we'd love to hear from you: research@protocol.ai
+ +Follow PL R&D and Protocol Labs for future publications, field maps, convenings, and opportunities to participate in the ecosystem as it continues to grow.
+ +This post is for informational purposes only. It is not an offer, solicitation, or recommendation of any security or investment product, and nothing here is a commitment or guarantee of any future performance or any outcome.
diff --git a/content/blog/preview-neurotech-ea88a298/index.md b/content/blog/preview-neurotech-ea88a298/index.md deleted file mode 100644 index 3182226b..00000000 --- a/content/blog/preview-neurotech-ea88a298/index.md +++ /dev/null @@ -1,203 +0,0 @@ ---- -title: "Neurotechnology: Bridging Minds and Machines for Human Flourishing" -date: 2026-08-22 -summary: "An overview of PL R&D's Neurotechnology focus area — brain-computer interfaces, biologically inspired AI, and whole-organism emulation — the three opportunity spaces we are backing, the inflection points we believe are within reach, and the 2030 milestones we are working toward." -authors: - - sean-escola - - david-markowitz -cover_image: "/images/blog/neurotechnology-hero.webp" -areas: - - neurotech -# Live at its URL, but kept out of the carousel, insights/blog listings, -# sitemap, RSS feed, and search index (and set to noindex). Flip to false -# (or remove) to publish it publicly. -unlisted: true ---- -Clinical BCI Superpower
-Brain-computer interfaces will demonstrate major improvements to the quality of life and capabilities of clinical patients — some of which will exceed the capabilities of healthy individuals.
-The BCI App Store
-We believe a major catalyst will occur when BCIs transition from vertically integrated medical products into open platforms. A standardized software layer that allows third-party developers to build applications on top of approved BCI hardware could dramatically increase the utility of neural interfaces. Just as smartphones became more valuable through app ecosystems, BCIs could unlock a wave of innovation once many developers can deploy neural augmentations through scalable software deployments.
-Neural Distillation
-One potential breakthrough is the emergence of methods that directly align AI systems with human neural activity. If neural recordings can help models learn more efficiently, or think in ways that better reflect human cognition, neural data could become a foundational resource for AI development. A specific inflection point would be 100,000,000 hours of human neural data recorded across cognitive tasks and recording device types.
-The Neuromorphic Energy Pivot
-A second possibility is that energy constraints push the AI industry toward biologically inspired hardware and algorithms. If brain-inspired systems achieve orders-of-magnitude improvements in efficiency vs current hardware or software designs, neuroscience could become a core driver of future AI progress.
-Memory Retrieval in Simulation
-The most catalytic milestone may be surprisingly simple. If a reconstructed mouse brain can be simulated and reliably reproduce a learned behavior or memory from its biological counterpart in a virtual environment, whole-organism emulation moves from speculation to demonstration. Such a result would establish a concrete benchmark for the field and fundamentally change how researchers, funders, and policymakers view the possibility and impact of emulation.
-![\"Securing](\"/images/blog/preview-dhr-f12c6df6/hero.webp\")
Part of a series introducing the focus areas of PL R&D.
\nOur information environment is being reshaped in real time by algorithms, networks, protocols, platforms, and adversaries that move faster than the institutions meant to govern them. Digital infrastructure, like core internet protocols, already shapes how we speak, gather, and keep our lives private. We now need to build the infrastructure that protects those freedoms faster, and more wisely, than that same infrastructure can be turned against them.
\nThe types of freedoms we mean are specific: freedom of speech (to seek, receive, and impart information regardless of frontiers); freedom of peaceful assembly and association; the right to privacy; recognition everywhere as a person before the law; and the freedom of thought and self-determination that underwrites them all. Far from new, each was hard-won through long debate.
\n![\"Juan](\"/images/blog/preview-dhr-f12c6df6/web3-summit-2019.png\")
At PL R&D, we know that the infrastructure we build today will determine which of these freedoms can be exercised tomorrow. To preserve and extend them, we invest in research, funding, and product development across four interconnected opportunity spaces. These are the frontiers where a technical breakthrough can become a durable protection for a specific right, rather than one more tool for eroding it.
\nWe organize our work into four layers, each sustaining specific rights:
\nThese layers stack. Resilient communication is the base every other right assumes; on top of it, portable identity establishes who you are without renting that standing from a platform or state; verifiable knowledge lets a public record prove its own integrity; and open agency and governance decide whether the AI acting on your behalf extends your control or concentrates it in a few hands.
\nEach layer rests on the one below it — resilient communication at the base, up through identity, verifiable knowledge, and open agency & governance.
\n![\"Censorship-Resistant](\"/images/opportunity-spaces/censorship-resistant-communications.jpg\")
Keeping communication and connectivity alive even in low-connectivity, partitioned, or adversarial environments. The frontier has moved past simple encryption toward metadata-resistance (hiding not just what you say but whom you say it to) and partition-tolerance (staying connected when the network is deliberately fragmented).
\nSpeech and assembly are the first freedoms to go in any adversarial environment, and both assume you can reach other people — an assumption that residential and cellular networks, controlled by a few incumbents and the states that license them, can revoke at will.
\nNation-state-independent connectivity is appearing: low-earth-orbit satellite networks such as Starlink decouple a person's ability to get online from the institutions that govern local access. Metadata-resistant tooling such as Kohaku (Ethereum Foundation) is productionizing Private Information Retrieval and mix networks inside a wallet, so that messages — and the patterns of who contacts whom — leak as little as possible. And modular networking stacks such as libp2p let applications find one another and stay connected even when traditional rails fail.
\nCommunication that cannot be switched off
\nThe step-change comes when nation-state-independent connectivity and metadata-resistant messaging reach consumer scale, so that during a deliberate shutdown a measurable share of a population stays connected and able to organize. Observable, and not yet true: a global connectivity provider offers consumer-scale service without state licensing or identity gating, and a metadata-resistant messenger crosses tens of millions of users under real adversarial conditions. At that point, censoring who may speak or gather online becomes impractical rather than merely illegal.
\n![\"Portable](\"/images/opportunity-spaces/portable-identity-credentials.jpg\")
Verifiable credentials and portable reputation owned by the individual rather than the platform — for humans and, increasingly, for the agents acting on their behalf — without depending on a centralized government ID or on expert-level key management.
\nIdentity is how a person is recognized, and today that recognition is mostly rented from platforms and states: lose the account or the document and you lose the standing. Without portability, people are trapped in whatever platform first issued their identity; without privacy, identity becomes a surveillance dossier. This sustains recognition as a person before the law, and privacy.
\nOpen social protocols such as the Authenticated Transfer (AT) Protocol behind Bluesky give people a credible exit: identity and data bind to a portable identifier the user controls, so a whole social graph can move between providers without loss. Sybil-resistant systems such as World establish that someone is a unique human without tying that proof to a state document. And zero-knowledge credential systems — spanning age verification, passkeys, and verifiable credentials — let a person prove one specific claim while disclosing as little as possible.
\nPersonhood without the state in the loop
\nThe step-change comes when a service at real scale — more than 100 million people — verifies unique humans for everyday services without anchoring them to a nation-state identity or KYC. Observable, and not yet true: today's proof-of-personhood systems operate well below that scale and outside mainstream services. When one crosses it, recognition as a person need no longer be rented from a state or a platform, and privacy-preserving personhood becomes safe to build on.
\n![\"Verifiable](\"/images/opportunity-spaces/verifiable-public-knowledge.jpg\")
Durable, tamper-evident records and standards for non-intermediated trust: systems that can prove a knowledge artifact has not been altered, and keep proving it over time.
\nThe rights to seek, receive, and share information depend on a shared public record people can trust. The ability to prove a piece of information is authentic has always underpinned that record, and as AI-generated content floods the internet that ability gets far more fragile and far more urgent. As global truth gets harder to verify, trust retreats into small private circles — a dark forest in which a common, checkable account of what happened ceases to exist.
\nContent addressing, as in IPFS, gives every file a verifiable identifier derived from its contents, so a reader can confirm data is exactly what was published. Provenance frameworks such as Starling Lab establish verifiable chains of custody for journalism and historical records. Large-scale archives such as the Internet Archive preserve digital history at scale. And formal-verification systems such as Lean, with zero-knowledge proofs of execution, extend provenance from documents to the computations that produced them.
\nProvenance becomes the default for truth
\nThe step-change comes when content authenticity stops being optional. Observable, and not yet true: two consecutive generations of frontier AI models ship attested provenance tooling by default, and at least one major platform or archive adopts content-addressed provenance as the default for its public record. As synthetic content becomes indistinguishable from the real thing, a public record that can prove its own integrity becomes the precondition for accurate information meaning anything at all.
\n![\"Sovereign](\"/images/opportunity-spaces/sovereign-infrastructure-ai-agents.jpg\")
The open environment — compute, storage, and identity — that lets AI agents coordinate and transact on our behalf: open enough to be permissionless, accountable enough to keep humans in charge.
\nAI is becoming a powerful extension of each of us and of the institutions around us, and the open question is whether that capability stays under individual human control or concentrates in a few hands. An agent that acts on your behalf only extends your agency if you, and not a single platform, govern the compute, storage, and identity it runs on. This is where self-determination and freedom of thought are won or lost.
\nOpen storage markets such as Filecoin run on independent providers rather than one centralized host, so no single party can deny, alter, or lose your data. Fully homomorphic encryption environments such as Zama let computation run directly on encrypted data, so agents can coordinate in public without exposing what they hold. And open compute protocols such as Gensyn and Prime Intellect train models across independent, globally distributed hardware rather than inside a single lab.
\nAgents run on open rails
\nThe step-change comes when serious AI capability no longer requires a single provider's stack. Observable, and not yet true: a frontier-scale model is trained across independent, decentralized hardware rather than one company's cluster, or a meaningful share of agent-to-agent economic activity settles on open, permissionless compute, storage, and identity rather than inside one platform. At that point the rights architecture of the agent economy is set in the open rather than by whoever owns the cluster.
\nThe next few years will decide whether these freedoms are quietly curtailed or deliberately extended. Human freedom can be hollowed out when infrastructure is centralized, surveilled, or switched off, and PL R&D focuses on the root system a free digital society stands on. We do not build every piece; we connect them, and aim our toolkit — field-building communications, convenings, grants, venture support, and policy and standards work — at the blockers specific to this field. (That toolkit is described in the PL R&D Overview.) PL's foundational primitives here — IPFS, libp2p, and content-addressed data — are among the strongest in the portfolio.
\nIf you are working on any of these four layers, we want to hear from you:
\nWe invite you to explore the projects already contributing to this vision. Reach us at research@protocol.ai.
\nThe rights we refuse to lose will be defended in the infrastructure, or not at all. Join us.
\nThis post is for informational purposes only. It is not an offer, solicitation, or recommendation of any security or investment product, and nothing here is a commitment or guarantee of any future performance or any outcome.
\n", + "coverImage": "/images/blog/neurotechnology-hero.webp", + "html": "![\"Neurotechnology:](\"/images/blog/neurotechnology-hero.webp\")
At PL R&D, we focus on fields that have the potential to unlock transformative new capabilities for humanity. The PL Neuro Focus Area aims to accelerate breakthroughs within the fields of Neuroscience & Neurotechnology.
\nAdvances in neuroscience, brain-computer interfaces (BCIs), biologically inspired AI, and whole-brain emulation are accelerating rapidly. Together, they unlock a future where we can better understand intelligence, restore and expand human capabilities, and build entirely new forms of human-machine interaction. However, the field today remains fragmented: key technical, regulatory, infrastructure, and capital bottlenecks continue to slow progress. We aim to change that.
\nPL Neuro exists to break bottlenecks: to define the milestones neurotech and NeuroAI need, drive the research that shifts what's believed possible, and route talent and capital to some of humanity's hardest and most important problems.
\nWe focus on three opportunity spaces that could reshape both neuroscience and computing over the coming decade:
\nTogether, these areas form a loop: advances in neuroscience (via augmentation and mapping) generate new data and understanding; those insights enable more capable AI systems and neurotechnologies (NeuroAI applications); and progress across both creates entirely new possibilities for augmenting human cognition (improved augmentation & emulation).
\n![\"Neural](\"/images/opportunity-spaces/neural-augmentation.jpg\")
Neural augmentation focuses on building high-bandwidth, bidirectional interfaces between brains and computers.
\nNear-term applications are therapeutic: restoring communication, movement, and independence for people living with paralysis or neurological conditions. Longer-term, these same technologies may enable entirely new forms of interaction, communication, and cognition that extend human capability.
\nBCIs have already demonstrated life-changing benefits in clinical settings. The next challenge is moving from isolated medical devices to scalable platforms that support broad access and innovation.
\nKey areas of interest include:
\nMaking neural interfaces useful beyond a small number of research participants requires progress on several fronts: how much information they can carry, how invasively they interact with neural tissue, and how they reach patients through clinical care. Recent developments show movement on each, although the devices are at different stages of clinical and commercial development.
\nClinical BCI Superpower
\nBrain computer interfaces will demonstrate major improvements to the quality of life and capabilities of clinical patients - some of which will exceed the capabilities of healthy individuals - creating demand for BCIs beyond clinical applications to access these superpowers. This demand helps reach a major inflection point for BCI access and utility: 10,000 high-bandwidth neural implants in humans.
\nThe BCI App Store
\nWe believe a major catalyst will occur when BCIs transition from vertically integrated medical products into open platforms. A standardized software layer that allows third-party developers to build applications on top of approved BCI hardware could dramatically increase the utility of neural interfaces. Just as smartphones became more valuable through app ecosystems, BCIs could unlock a wave of innovation once many developers can deploy neural augmentations through scalable software deployments.
\n![\"Biologically](\"/images/opportunity-spaces/biologically-inspired-intelligence.jpg\")
NeuroAI seeks to use insights from biological intelligence to build more capable, efficient, and accessible AI systems.
\nRather than treating the brain as merely an object of study, NeuroAI treats it as a source of architectural, representational, and algorithmic inspiration. NeuroAI harnesses AI tools like large-scale data collection, simulation, benchmarking, and predictive models to better understand the brain and how it operates so efficiently.
\nModern AI carries enormous computational and energy cost.
\nBrains demonstrate that intelligence can emerge from systems that are dramatically more efficient than today's machine learning architectures. Understanding how biological intelligence works may help unlock and align the next generation of AI.
\nAreas we find particularly promising include:
\nUsing neuroscience to improve AI depends on data that connects neural structure to function, and models that can extract useful patterns from those observations. Recent work is making both more accessible to researchers, with shared datasets and predictive models that allow theories of biological computation to be tested at larger scales.
\nNeural Distillation
\nOne potential breakthrough is the emergence of methods that directly align AI systems with human neural activity. If neural recordings can help models learn more efficiently, or think in ways that better reflect human cognition, neural data could become a foundational resource for AI development. A specific inflection point would be 100,000,000 hours of human neural data recorded across cognitive tasks and recording device types.
\nThe Neuromorphic Energy Pivot
\nA second possibility is that energy constraints push the AI industry toward biologically inspired hardware and algorithms. If brain-inspired systems achieve orders-of-magnitude improvements in efficiency vs current hardware or software designs, neuroscience could become a core driver of future AI progress.
\n![\"Whole-Organism](\"/images/opportunity-spaces/whole-organism-emulation.jpg\")
Whole organism emulation (also known as Whole Brain Emulation (WBE)) seeks to create computational models that reproduce the behavior of biological organisms using detailed neural and biological data.
\nWhile often discussed as science fiction, the field is increasingly becoming an engineering challenge shaped by advances in connectomics, imaging, simulation, and neuroscience.
\nA successful emulation system would provide an unprecedented tool for understanding intelligence, learning, memory, and behavior.
\nIt could also dramatically accelerate neuroscience by enabling experiments that are difficult (or impossible) to perform in living systems.
\nPromising areas include:
\nThree major constraints sit between a fixed brain and a running simulation: how much tissue can be imaged, how much human labor reconstruction takes, and whether structural data is sufficient to specify function. Significant progress has been made against all three constraints in the past year.
\nMemory Retrieval in Simulation
\nThe most catalytic milestone may be surprisingly simple.
\nIf a reconstructed brain or organoid can be simulated and reliably reproduce a specific learned behavior or memory from its biological counterpart in a virtual environment, whole-brain emulation moves from speculation to demonstration. Such a result would establish a concrete benchmark for the field and fundamentally change how researchers, funders, and policymakers view the possibility and impact of emulation.
\nMouse Brain Connectome
\nMapping and emulating a whole mouse connectome would be a crucial stepping stone to understanding how mammalian brains process information, and how physical connections and synapses translate into real-time brain activity, perception, and behavior. It would also provide a platform for studying mammalian synaptic plasticity—how experience changes the strength and organization of connections between neurons—and how these changes enable learning. Finally, an effort at this scale would also solidify methods and drive cost-curve improvements to make human-brain mapping feasible.
\nBreakthroughs do not emerge from technology alone. They require healthy ecosystems that connect research institutions, domain experts, capital allocators, startup founders, and more.
\nToday, neurotechnology faces fragmentation across disciplines, institutions, and stakeholder groups. Researchers, founders, funders, policymakers, and engineers often operate in separate communities despite working toward related goals.
\nBuilding the field itself is therefore a critical leverage point. Our field-building strategy centers on:
\nA stronger ecosystem increases the likelihood that advances in BCI, NeuroAI, and emulation reinforce one another rather than developing in isolation.
\nThe coming decade could determine whether neurotechnology remains a niche scientific endeavor or becomes one of the defining technological frontiers of the century. We believe the field is approaching several important inflection points:
\nReaching them will require coordinated effort across research, entrepreneurship, policy, infrastructure, and capital. PL R&D exists to help accelerate that coordination.
\nWe're actively building relationships with researchers, founders, funders, policymakers, and technologists working across neurotechnology, NeuroAI, connectomics, and related fields. You can see our latest work (including roadmaps, podcasts, and more) at plneuro.xyz.
\nIf you're interested in contributing to the future of neurotechnology or would like to attend a future PL Neuro event, we'd love to hear from you: research@protocol.ai
\nFollow PL R&D and Protocol Labs for future publications, field maps, convenings, and opportunities to participate in the ecosystem as it continues to grow.
\nThis post is for informational purposes only. It is not an offer, solicitation, or recommendation of any security or investment product, and nothing here is a commitment or guarantee of any future performance or any outcome.
\n", "unlisted": true }, { - "slug": "preview-neurotech-ea88a298", - "title": "Neurotechnology: Bridging Minds and Machines for Human Flourishing", - "date": "2026-08-22T00:00:00.000Z", - "summary": "An overview of PL R&D's Neurotechnology focus area — brain-computer interfaces, biologically inspired AI, and whole-organism emulation — the three opportunity spaces we are backing, the inflection points we believe are within reach, and the 2030 milestones we are working toward.", + "slug": "preview-dhr-f12c6df6", + "title": "Securing Fundamental Rights in the Digital Realm: The Infrastructure Freedom Now Runs On", + "date": "2026-08-30T00:00:00.000Z", + "summary": "The digital foundations our fundamental rights now depend on — censorship-resistant communication, portable identity, verifiable public knowledge, and sovereign infrastructure for AI and agents — the four opportunity spaces we are backing and the inflection points we believe are within reach.", "description": "", "authors": [ - "sean-escola", - "david-markowitz" + "will-scott" ], "areas": [ - "neurotech" + "digital-human-rights" ], "external_url": "", - "coverImage": "/images/blog/neurotechnology-hero.webp", - "html": "At PL R&D, we focus on fields that have the potential to unlock transformative new capabilities for humanity. The PL Neuro Focus Area aims to accelerate computing breakthroughs within the fields of neuroscience and neurotechnology.
\nAdvances in neuroscience, brain-computer interfaces (BCIs), biologically inspired AI, and whole-organism emulation are accelerating rapidly. Together, they unlock a future where we can better understand intelligence, restore and expand human capabilities, and build entirely new forms of human-machine interaction. However, the field today remains fragmented: key technical, regulatory, infrastructure, and capital bottlenecks continue to slow progress. We aim to change that.
\nPL Neuro's mission is to help secure a future of human flourishing by bridging minds and machines in ways that expand human potential while preserving autonomy, dignity, and individual agency.
\nWe focus on three opportunity spaces that could reshape both neuroscience and computing over the coming decade:
\nTogether, these areas form a loop: advances in neuroscience generate new data and understanding; those insights enable more capable AI systems and neurotechnologies; and progress across both creates entirely new possibilities for augmenting human cognition.
\nNeural augmentation focuses on building high-bandwidth, bidirectional interfaces between brains and computers.
\nNear-term applications are therapeutic: restoring communication, movement, and independence for people living with paralysis or neurological conditions. Longer-term, these same technologies may enable entirely new forms of interaction, communication, and cognition.
\nBCIs have already demonstrated life-changing benefits in clinical settings. The next challenge is moving from isolated medical devices to scalable platforms that support broad innovation.
\nKey areas of interest include:
\nClinical BCI Superpower
\nBrain-computer interfaces will demonstrate major improvements to the quality of life and capabilities of clinical patients — some of which will exceed the capabilities of healthy individuals.
\nThe BCI App Store
\nWe believe a major catalyst will occur when BCIs transition from vertically integrated medical products into open platforms. A standardized software layer that allows third-party developers to build applications on top of approved BCI hardware could dramatically increase the utility of neural interfaces. Just as smartphones became more valuable through app ecosystems, BCIs could unlock a wave of innovation once many developers can deploy neural augmentations through scalable software deployments.
\nNeuroAI seeks to use insights from biological intelligence to build more capable, efficient, and accessible AI systems.
\nRather than treating the brain as merely an object of study, NeuroAI treats it as a source of architectural, representational, and algorithmic inspiration.
\nModern AI carries enormous computational and energy cost.
\nBrains demonstrate that intelligence can emerge from systems that are dramatically more efficient than today's machine learning architectures. Understanding how biological intelligence works may help unlock the next generation of AI.
\nAreas we find particularly promising include:
\nNeural Distillation
\nOne potential breakthrough is the emergence of methods that directly align AI systems with human neural activity. If neural recordings can help models learn more efficiently, or think in ways that better reflect human cognition, neural data could become a foundational resource for AI development. A specific inflection point would be 100,000,000 hours of human neural data recorded across cognitive tasks and recording device types.
\nThe Neuromorphic Energy Pivot
\nA second possibility is that energy constraints push the AI industry toward biologically inspired hardware and algorithms. If brain-inspired systems achieve orders-of-magnitude improvements in efficiency vs current hardware or software designs, neuroscience could become a core driver of future AI progress.
\nWhole organism emulation seeks to create computational models that reproduce the behavior of biological organisms using detailed neural and biological data.
\nWhile often discussed as science fiction, the field is increasingly becoming an engineering challenge shaped by advances in connectomics, imaging, simulation, and neuroscience.
\nA successful emulation system would provide an unprecedented tool for understanding intelligence, learning, memory, and behavior.
\nIt could also dramatically accelerate neuroscience by enabling experiments that are difficult (or impossible) to perform in living systems.
\nPromising areas include:
\nThree major constraints sit between a fixed brain and a running simulation: how much tissue can be imaged, how much human labor reconstruction takes, and whether structural data is sufficient to specify function. Significant progress has been made against all three constraints in the past year.
\nOn imaging, moving off electron microscopy changes the cost curve. A team at the Institute of Science and Technology Austria published a light-microscopy pipeline that expands tissue roughly 16-fold. Light microscopes are cheaper and far more widely installed than electron microscopes, and the method leaves room for molecular labels that electron microscopy cannot read.
\nOn reconstruction, the binding cost at mouse scale is human proofreading hours. Janelia's PATHFINDER pipeline reports 94.2% normalized expected run length for exhaustive axon reconstruction and an 84-fold reduction in projected proofreading cost against prior work.
\nOn sufficiency, the field's hardest open question is whether a connectome constrains dynamics tightly enough to simulate. A recent preprint proposes an ultrastructure-to-dynamics compiler. If mappings like this hold, molecular annotation plus a connectome becomes enough to parameterize a simulation.
\nMemory Retrieval in Simulation
\nThe most catalytic milestone may be surprisingly simple. If a reconstructed mouse brain can be simulated and reliably reproduce a learned behavior or memory from its biological counterpart in a virtual environment, whole-organism emulation moves from speculation to demonstration. Such a result would establish a concrete benchmark for the field and fundamentally change how researchers, funders, and policymakers view the possibility and impact of emulation.
\nBreakthroughs do not emerge from technology alone. They require healthy ecosystems that connect research institutions, domain experts, capital allocators, startup founders, and more.
\nToday, neurotechnology faces fragmentation across disciplines, institutions, and stakeholder groups. Researchers, founders, funders, policymakers, and engineers often operate in separate communities despite working toward related goals.
\nBuilding the field itself is therefore a critical leverage point. Our field-building strategy centers on:
\nA stronger ecosystem increases the likelihood that advances in BCI, NeuroAI, and emulation reinforce one another rather than developing in isolation.
\nThe coming decade could determine whether neurotechnology remains a niche scientific endeavor or becomes one of the defining technological frontiers of the century. We believe the field is approaching several important inflection points:
\nReaching them will require coordinated effort across research, entrepreneurship, policy, infrastructure, and capital. PL R&D exists to help accelerate that coordination.
\nWe're actively building relationships with researchers, founders, funders, policymakers, and technologists working across neurotechnology, NeuroAI, connectomics, and related fields.
\nIf you're interested in contributing to the future of neurotechnology, we'd love to hear from you: research@protocol.ai.
\nFollow PL R&D and Protocol Labs for future publications, field maps, convenings, and opportunities to participate in the ecosystem as it continues to grow.
\nThis post is for informational purposes only. It is not an offer, solicitation, or recommendation of any security or investment product, and nothing here is a commitment or guarantee of any future performance or any outcome.
\n", + "coverImage": "/images/blog/preview-dhr-f12c6df6/hero.webp", + "html": "Part of a series introducing the focus areas of PL R&D.
\nOur information environment is being reshaped in real time by algorithms, networks, protocols, platforms, and adversaries that move faster than the institutions meant to govern them. Digital infrastructure, like core internet protocols, already shapes how we speak, gather, and keep our lives private. We now need to build the infrastructure that protects those freedoms faster, and more wisely, than that same infrastructure can be turned against them.
\nThe types of freedoms we mean are specific: freedom of speech (to seek, receive, and impart information regardless of frontiers); freedom of peaceful assembly and association; the right to privacy; recognition everywhere as a person before the law; and the freedom of thought and self-determination that underwrites them all. Far from new, each was hard-won through long debate.
\nAt PL R&D, we know that the infrastructure we build today will determine which of these freedoms can be exercised tomorrow. To preserve and extend them, we invest in research, funding, and product development across four interconnected opportunity spaces. These are the frontiers where a technical breakthrough can become a durable protection for a specific right, rather than one more tool for eroding it.
\nWe organize our work into four layers, each sustaining specific rights:
\nThese layers stack. Resilient communication is the base every other right assumes; on top of it, portable identity establishes who you are without renting that standing from a platform or state; verifiable knowledge lets a public record prove its own integrity; and open agency and governance decide whether the AI acting on your behalf extends your control or concentrates it in a few hands.
\nEach layer rests on the one below it — resilient communication at the base, up through identity, verifiable knowledge, and open agency & governance.
\nKeeping communication and connectivity alive even in low-connectivity, partitioned, or adversarial environments. The frontier has moved past simple encryption toward metadata-resistance (hiding not just what you say but whom you say it to) and partition-tolerance (staying connected when the network is deliberately fragmented).
\nSpeech and assembly are the first freedoms to go in any adversarial environment, and both assume you can reach other people — an assumption that residential and cellular networks, controlled by a few incumbents and the states that license them, can revoke at will.
\nNation-state-independent connectivity is appearing: low-earth-orbit satellite networks such as Starlink decouple a person's ability to get online from the institutions that govern local access. Metadata-resistant tooling such as Kohaku (Ethereum Foundation) is productionizing Private Information Retrieval and mix networks inside a wallet, so that messages — and the patterns of who contacts whom — leak as little as possible. And modular networking stacks such as libp2p let applications find one another and stay connected even when traditional rails fail.
\nCommunication that cannot be switched off
\nThe step-change comes when nation-state-independent connectivity and metadata-resistant messaging reach consumer scale, so that during a deliberate shutdown a measurable share of a population stays connected and able to organize. Observable, and not yet true: a global connectivity provider offers consumer-scale service without state licensing or identity gating, and a metadata-resistant messenger crosses tens of millions of users under real adversarial conditions. At that point, censoring who may speak or gather online becomes impractical rather than merely illegal.
\nVerifiable credentials and portable reputation owned by the individual rather than the platform — for humans and, increasingly, for the agents acting on their behalf — without depending on a centralized government ID or on expert-level key management.
\nIdentity is how a person is recognized, and today that recognition is mostly rented from platforms and states: lose the account or the document and you lose the standing. Without portability, people are trapped in whatever platform first issued their identity; without privacy, identity becomes a surveillance dossier. This sustains recognition as a person before the law, and privacy.
\nOpen social protocols such as the Authenticated Transfer (AT) Protocol behind Bluesky give people a credible exit: identity and data bind to a portable identifier the user controls, so a whole social graph can move between providers without loss. Sybil-resistant systems such as World establish that someone is a unique human without tying that proof to a state document. And zero-knowledge credential systems — spanning age verification, passkeys, and verifiable credentials — let a person prove one specific claim while disclosing as little as possible.
\nPersonhood without the state in the loop
\nThe step-change comes when a service at real scale — more than 100 million people — verifies unique humans for everyday services without anchoring them to a nation-state identity or KYC. Observable, and not yet true: today's proof-of-personhood systems operate well below that scale and outside mainstream services. When one crosses it, recognition as a person need no longer be rented from a state or a platform, and privacy-preserving personhood becomes safe to build on.
\nDurable, tamper-evident records and standards for non-intermediated trust: systems that can prove a knowledge artifact has not been altered, and keep proving it over time.
\nThe rights to seek, receive, and share information depend on a shared public record people can trust. The ability to prove a piece of information is authentic has always underpinned that record, and as AI-generated content floods the internet that ability gets far more fragile and far more urgent. As global truth gets harder to verify, trust retreats into small private circles — a dark forest in which a common, checkable account of what happened ceases to exist.
\nContent addressing, as in IPFS, gives every file a verifiable identifier derived from its contents, so a reader can confirm data is exactly what was published. Provenance frameworks such as Starling Lab establish verifiable chains of custody for journalism and historical records. Large-scale archives such as the Internet Archive preserve digital history at scale. And formal-verification systems such as Lean, with zero-knowledge proofs of execution, extend provenance from documents to the computations that produced them.
\nProvenance becomes the default for truth
\nThe step-change comes when content authenticity stops being optional. Observable, and not yet true: two consecutive generations of frontier AI models ship attested provenance tooling by default, and at least one major platform or archive adopts content-addressed provenance as the default for its public record. As synthetic content becomes indistinguishable from the real thing, a public record that can prove its own integrity becomes the precondition for accurate information meaning anything at all.
\nThe open environment — compute, storage, and identity — that lets AI agents coordinate and transact on our behalf: open enough to be permissionless, accountable enough to keep humans in charge.
\nAI is becoming a powerful extension of each of us and of the institutions around us, and the open question is whether that capability stays under individual human control or concentrates in a few hands. An agent that acts on your behalf only extends your agency if you, and not a single platform, govern the compute, storage, and identity it runs on. This is where self-determination and freedom of thought are won or lost.
\nOpen storage markets such as Filecoin run on independent providers rather than one centralized host, so no single party can deny, alter, or lose your data. Fully homomorphic encryption environments such as Zama let computation run directly on encrypted data, so agents can coordinate in public without exposing what they hold. And open compute protocols such as Gensyn and Prime Intellect train models across independent, globally distributed hardware rather than inside a single lab.
\nAgents run on open rails
\nThe step-change comes when serious AI capability no longer requires a single provider's stack. Observable, and not yet true: a frontier-scale model is trained across independent, decentralized hardware rather than one company's cluster, or a meaningful share of agent-to-agent economic activity settles on open, permissionless compute, storage, and identity rather than inside one platform. At that point the rights architecture of the agent economy is set in the open rather than by whoever owns the cluster.
\nThe next few years will decide whether these freedoms are quietly curtailed or deliberately extended. Human freedom can be hollowed out when infrastructure is centralized, surveilled, or switched off, and PL R&D focuses on the root system a free digital society stands on. We do not build every piece; we connect them, and aim our toolkit — field-building communications, convenings, grants, venture support, and policy and standards work — at the blockers specific to this field. (That toolkit is described in the PL R&D Overview.) PL's foundational primitives here — IPFS, libp2p, and content-addressed data — are among the strongest in the portfolio.
\nIf you are working on any of these four layers, we want to hear from you:
\nWe invite you to explore the projects already contributing to this vision. Reach us at research@protocol.ai.
\nThe rights we refuse to lose will be defended in the infrastructure, or not at all. Join us.
\nThis post is for informational purposes only. It is not an offer, solicitation, or recommendation of any security or investment product, and nothing here is a commitment or guarantee of any future performance or any outcome.
\n", "unlisted": true }, { @@ -109,7 +109,7 @@ "digital-human-rights" ], "external_url": "https://protocol.ai/blog/data-sovereignty-in-a-privacy-first-future/", - "coverImage": "https://protocol.ai/images/blog/og/data-sovereignty-in-a-privacy-first-future.jpg", + "coverImage": "https://pl.xyz/images/blog/og/data-sovereignty-in-a-privacy-first-future.jpg", "html": "", "unlisted": false }, @@ -122,7 +122,7 @@ "authors": [], "areas": [], "external_url": "https://protocol.ai/blog/attestation-follow-in-the-footsteps-of-tls/", - "coverImage": "https://protocol.ai/images/blog/og/attestation-follow-in-the-footsteps-of-TLS.png", + "coverImage": "https://pl.xyz/images/blog/og/attestation-follow-in-the-footsteps-of-TLS.png", "html": "", "unlisted": false }, @@ -135,7 +135,7 @@ "authors": [], "areas": [], "external_url": "https://protocol.ai/blog/threads-from-the-2025-cypherpunk-retreat/", - "coverImage": "https://protocol.ai/images/blog/og/cyber-punk-retreat.jpg", + "coverImage": "https://pl.xyz/images/blog/og/cyber-punk-retreat.jpg", "html": "", "unlisted": false }, @@ -150,7 +150,7 @@ "ai-robotics" ], "external_url": "https://protocol.ai/blog/bit-robot-and-the-future-of-embodied-ai/", - "coverImage": "https://protocol.ai/images/blog/og/bit-robot.jpg", + "coverImage": "https://pl.xyz/images/blog/og/bit-robot.jpg", "html": "", "unlisted": false }, @@ -163,7 +163,7 @@ "authors": [], "areas": [], "external_url": "https://protocol.ai/blog/the-impact-of-our-innovation-network/", - "coverImage": "https://protocol.ai/images/blog/og/pl-summit-2024.jpg", + "coverImage": "https://pl.xyz/images/blog/og/pl-summit-2024.jpg", "html": "", "unlisted": false }, @@ -178,7 +178,7 @@ "neurotech" ], "external_url": "https://protocol.ai/blog/the-transformative-power-of-neurotechnology/", - "coverImage": "https://protocol.ai/images/blog/og/pl-blog-future-neurotech.jpg", + "coverImage": "https://pl.xyz/images/blog/og/pl-blog-future-neurotech.jpg", "html": "", "unlisted": false }, @@ -191,7 +191,7 @@ "authors": [], "areas": [], "external_url": "https://protocol.ai/blog/transcription-pl-vision-driving-a-breakthroughs-in-computing-to-push-humanity-forward/", - "coverImage": "https://protocol.ai/images/blog/og/pl-vision.png", + "coverImage": "https://pl.xyz/images/blog/og/pl-vision.png", "html": "", "unlisted": false }