Co-founder and Head of R&D at @servamind. AI and Machine Learning researcher, specifically in Hyperdimensional Computing and applications surrounding it.

Greenbelt, MD
Joined February 2026
Hi! I'm Peter, Co-founder and Head of R&D at @servamind. Throughout my PhD, I've focused on figuring out how to transfer the radical efficiency of Hyperdimensional Computing to the type of Artificial Intelligence we've grown accustomed to.
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Servamind got a shout out from Fundable today in their list of top 10 pre-seed rounds last week :)
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Servamind has raised its pre-seed. Grateful to everyone who backed us this early.
Servamind has raised a $1.2M pre-seed round, led by Davidovs Venture Collective. We build the new infrastructure beneath AI models, so you can run any of them at 10x the scale. Huge thank you to all our investors: @msdavidova, @Nick_Davidov, @dvc_collective, @Arrington_Cap, @EdgeCapitalMgmt, @EdgeVenturesVC, @PsalionVC, @web3funfunding Read the announcement below 👇
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Peter Sutor Jr retweeted
Come find us at our booth on tuesday!
Servamind is coming to Bits & Pretzels in Munich, September 28–30. If you're training or fine-tuning AI, we should have a chat! @bitsandpretzels
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Most people know Rachel St. Clair as the CEO of Servamind. Fewer know the research behind it: a PhD on catastrophic forgetting, peer-reviewed work on machine consciousness, an AGI-24 keynote. Details in the article linked below 👇
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Most companies in AI work above the model. We went underneath it, to how information is represented before a model ever sees it. Rachel @drrachelstclair wrote an article about what that means.
What is Servamind? Our Co-Founder and CEO Rachel St. Clair @drrachelstclair explains what we are building and what you can use today. Link below 👇
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Many of my papers explored what can be done immediately through plugging hypervectors into the AI pipeline. For those interested in reading them, there should be a free version of each on my Google Scholar, which I will link below.
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caught a candidate cheating at an ML system design interview today. He was talking without thinking. And I can see that from the first three minutes, but I let him talk. We went through the entire design end-to-end. Then I invited him to share the screen and draw the architecture. He froze. Then I saw a chatbot window flickering. i had to terminate the interview. For people who cheat, what is on their mind? Why not buy more reliable cheating software? Isn't it very obvious?
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Peter Sutor Jr retweeted
Enormous, imo.
New lecture drop 🎓 In our latest "Learning from Bio to AI" session, Andrew Coward explores Procedural Memory—how the brain learns skills and sequences. Join us tomorrow 7pm EST for a live Q&A on X Spaces to dig deeper. 🎥 Watch now
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Peter Sutor Jr retweeted
Encode once, compute anywhere
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Peter Sutor Jr retweeted
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Peter Sutor Jr retweeted
Tired of pre-processing your data? Us too... Use Serva Encoder to forever pre-process any data for any AI.
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Peter Sutor Jr retweeted
Servastack means no more padding, any shape, for mixed datasets, all to one file format, all to one AI without messy reshaping. Auto-pad is here.
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Peter Sutor Jr retweeted
AI teams spend 80% of their time on data prep—not building models. We built .serva: one data format that works with any model, on any hardware.30-374× more energy efficient. 4-34× compression. No retraining needed. The bottleneck shifts from infrastructure to imagination.
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Peter Sutor Jr retweeted
Your AI team isn't slow because of your models. They're slow because 80% of their time goes to data wrangling. .serva collapses months of preprocessing into a single encoding step. Any data → any model → any hardware See the architecture: arxiv.org/abs/2601.09124
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Peter Sutor Jr retweeted
We're looking for pilot partners to validate .serva in production. If your team: Trains models regularly Fights data preprocessing bottlenecks Wants 30-374× energy efficiency without retraining Let's talk. Early partners shape the roadmap. DM us or: [email protected]
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