Just back from a truly impactful few days at Asilomar for the Brain and Mind, hosted by the brilliant team at BrainMind. The spirit of the 1975 Recombinant DNA Conference felt palpable as we gathered to chart ethical standards for the accelerating field of Neurotech. While our focus was on neuroethics, from investor diligence questions and board-level risk matrices to user/stakeholder engagement and toolkits for neuroentrepreneurs, the key themes shared a powerful parallel with AI Ethics: maintain and enhance human agency, combat misuse and mistrust, and acknowledge that innovation is moving faster than its guardrails. Both fields present novel challenges that demand we adapt our existing frameworks and principles to meet new challenges. At the heart of it all is human agency. Whether we're discussing neurodevices or large language models, our core responsibility as builders, executives, investors, and policymakers is to ensure people are informed, in control, and never burdened to fight for their own empowerment or autonomy. We have the fundamental responsibility to care about the people we serve. This commitment to responsible, human-centric development is fundamental to our work at Inflection AI. We're building with emotional intelligence at the core. Every product decision we make starts with a simple question: does this expand what people can do, or does it quietly shift the burden onto them? AI should work for the humans using it, amplifying judgment, not replacing it. Earning trust through transparency rather than demanding it through dependency. A special thank you to Diana Saville for once again outdoing herself at every event and to Michael McCullough, MD for his endless support of the ecosystem. And to all the Braingels who showed up and rolled up their sleeves! Let's translate the urgency from Asilomar into action and continue to drive positive change.
Why A Neurotech VC Bet On Anthropic: Intelligence, Interpretability, and the NeuroAI Stack — Kaleida Capital
Why would a neurotech VC bet on Anthropic? This article examines how frontier AI, neuroscience, model behavior, and intelligent systems intersect within Kaleida Capital’s NeuroAI thesis and the infrastructure shaping next-generation intelligence.
#digitalbrainproject #neuroscience #artificialintelligence #openscience #callforprojects #research #ai #brain | Fondation Adolphe de Rothschild
The Rothschild Foundation Hospital is excited to launch the Digital Brain Project, a $5M collaborative research initiative to build an open source foundational model of the brain through open-access neural data. Apply by May 15th for up to $500k in funding. Help crack the neural code 👉digitalbrainproject.org Our objective is to develop a standardized, publicly available dataset of human brain recordings to accelerate fundamental research in cognitive neuroscience, AI system development, and clinical health. Our independent, multidisciplinary Scientific Committee oversees data collection, ethical review, privacy, and open science practices of our project — setting standards for large-scale brain research. The Digital Brain Project is conceived as an open collaborative infrastructure, at the intersection of neuroscience, artificial intelligence, and data science. It aims to accelerate data development, a key bottleneck to developing a foundational AI model of the human brain. Key Focus Areas: 1️⃣ Brain recording data related to visual processing, language functions and cognitive actions 2️⃣ Rigorous quality, privacy, and ethical control, along with procedures for standardizing data across sites 3️⃣ Support for teams selected by an international multidisciplinary Scientific Committee Call for applications: Research teams working in neuroscience, neuroimaging, or artificial intelligence are invited to submit their applications by May 15, 2026. Selected teams will receive up to $500k USD funding to support their work. We appreciate our Scientific Committee (Lune Bellec Anne-Marie Kermarrec Arthur Mensch Russell Poldrack Lucia Melloni Jose Alain Sahel) for their independent scientific leadership, and partners Université de Montréal and AI at Meta for collaborating on this exciting project. #DigitalBrainProject #Neuroscience #ArtificialIntelligence #OpenScience #Callforprojects #Research #AI #Brain -------------------------------------------------------------- Pierre Bourdillon Julie Boyle Elisa Cascardi Jean-Rémi King Guillaume Le Hénanff Amélie Yavchitz Julien Gottsmann Fabrice VERRIELE Charlotte Cardin-Taillia
NeuroNYC
As the global leader in finance, policy, art, research, and medicine, the region is well-positioned to lead neurotech. We help foster and promote the local neurotech ecosystem: clinics, companies, funders, labs, and users.
ETCH
We believe technology should serve humanity and that human creativity is essential and irreplaceable. We support the ethical development and deployment of AI by funding protective technologies and translating research into real-world tools for creative communities.
Jeff Bezos Is Funding a Wild Hunt for the Brain’s ‘Core Algorithm’
With $500 million in funding and a reported $2.5 billion valuation, Flourish wants to reinvent AI by putting real neurons under the microscope.
BrainMind
At this important juncture in neuroscience, the BrainMind ecosystem is combining the most talented of these groups in novel ways to collectively shepherd, support, and fund ideas that can be translated from labs into interventions that will benefit humanity.
Brainrot: Deskilling and Addiction are Overlooked AI Risks | Proceedings of the 2026 ACM Conference on Fairness, Accountability, and Transparency
As part of the Digital Library's transition to Open Access, new features for researchers are available in the Premium Edition. Click here to learn more.
Inventing the future: A neuroscience research roadmap
The past decade of transformative advances in neurotechnology portends an exciting future for neuroscience. This NeuroView charts a strategic path to accelerate and integrate research discovery and speed the development of new cures for human brain disorders.
Yneuro | The startup behind Neuro ID®
Imagine a world where technology and human experience blend seamlessly. At Yneuro, we’re building that world. As pioneers in neurotechnology, we craft AI-driven software solutions that transcend global barriers. Celebrated in startup ecosystems and competitions, Yneuro is redefining digital interaction, making advanced technologies intuitive and accessible for everyone. Join us as we merge technology and human cognition, creating unprecedented possibilities.
Funding and Framing Impact in the Neuro Frontier
Representations 04: Philanthropy, FRO, Connectomes, ARIA
Introducing TRIBE v2: A Predictive Foundation Model Trained to Understand How the Human Brain Processes Complex Stimuli | Keith Doelling
This is some very cool work by some awesome colleagues Jean-Rémi King, and Teon Brooks! Seriously not enough good things can be said about how cool it is. You should enjoy it and play with it. And kudos to Meta for open sourcing it. At the same time, I'm already seeing posts about how the model will replace fMRI experiments as researchers will simulate how the brain "really works" instead of running costly experiments. I think this goes WELL beyond what its creators intend. We are already seeing that use of AI in science allows you to explore charted ideas more thoroughly and much more rapidly but slows us down in finding novel ideas (https://lnkd.in/eMR2akqt). At the same time, there is growing concern that LLM performance will collapse as they are increasingly trained on their own output (https://lnkd.in/eavgfyuY). Leaving neuroscience to AI simulations risks following the same fate, where we generate seemingly new findings without gaining new meaning. A mechanistic understanding of how the brain works (if that is still your goal) will be found at the margins, in errors and idiosyncrasies of neural function. What TRIBE provides is a super useful and cool instantiation of our current understanding on how and where neural activity is instantiated in the brain. But it won't help us make groundbreaking new findings of how neural circuits lead to cognition and behavior. Experiments on real human brains, may be costly, but they will always be necessary!
Introducing TRIBE v2: A Predictive Foundation Model Trained to Understand How the Human Brain Processes Complex Stimuli | Keith Doelling
This is some very cool work by some awesome colleagues Jean-Rémi King, and Teon Brooks! Seriously not enough good things can be said about how cool it is. You should enjoy it and play with it. And kudos to Meta for open sourcing it. At the same time, I'm already seeing posts about how the model will replace fMRI experiments as researchers will simulate how the brain "really works" instead of running costly experiments. I think this goes WELL beyond what its creators intend. We are already seeing that use of AI in science allows you to explore charted ideas more thoroughly and much more rapidly but slows us down in finding novel ideas (https://lnkd.in/eMR2akqt). At the same time, there is growing concern that LLM performance will collapse as they are increasingly trained on their own output (https://lnkd.in/eavgfyuY). Leaving neuroscience to AI simulations risks following the same fate, where we generate seemingly new findings without gaining new meaning. A mechanistic understanding of how the brain works (if that is still your goal) will be found at the margins, in errors and idiosyncrasies of neural function. What TRIBE provides is a super useful and cool instantiation of our current understanding on how and where neural activity is instantiated in the brain. But it won't help us make groundbreaking new findings of how neural circuits lead to cognition and behavior. Experiments on real human brains, may be costly, but they will always be necessary!
Taking AI Welfare Seriously
In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. That means that the prospect of AI welfare and moral patienthood, i.e. of AI systems with their own interests and moral significance, is no longer an issue only for sci-fi or the distant future. It is an issue for the near future, and AI companies and other actors have a responsibility to start taking it seriously. We also recommend three early steps that AI companies and other actors can take: They can (1) acknowledge that AI welfare is an important and difficult issue (and ensure that language model outputs do the same), (2) start assessing AI systems for evidence of consciousness and robust agency, and (3) prepare policies and procedures for treating AI systems with an appropriate level of moral concern. To be clear, our argument in this report is not that AI systems definitely are, or will be, conscious, robustly agentic, or otherwise morally significant. Instead, our argument is that there is substantial uncertainty about these possibilities, and so we need to improve our understanding of AI welfare and our ability to make wise decisions about this issue. Otherwise there is a significant risk that we will mishandle decisions about AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly caring for AI systems that do not.
Debates over AI consciousness are a trap
If AI systems are viewed as too advanced to control, the companies that build them can’t held liable for the harms they cause.
Introducing TRIBE v2: A Predictive Foundation Model Trained to Understand How the Human Brain Processes Complex Stimuli
Understanding how the human brain processes the world around us is one of the greatest open challenges in neuroscience. Breakthroughs here could transform how we understand and treat neurological conditions affecting hundreds of millions of people — and improve AI systems by directly guiding their development from neuroscientific principles.
Massively Scalable Neurotechnologies
Backed by £50m, this programme sits within the Scalable Neural Interfaces opportunity space and is seeking radically new ways to deliver responsive neurotechnologies to the brain without brain surgery.