David Herel profile picture

David Herel

Co-Founder @ BottleCap AI

Hi, I’m David. I’m a co-founder at BottleCap AI, where we work on making large language models dramatically faster and cheaper to train and run.

I also co-founded Hive Spirit Technologies with Tomas Mikolov, building language models for algorithmic trading on stock markets. My research is in language models and LLM reasoning. I’m a co-inventor of Thinking Tokens, the idea behind the thinking mode in today’s chatbots, and have papers at ICLR, ECAI, Amazon Science and ALIFE. I continued this work as a visiting researcher at NUS and was a finalist in Amazon’s Alexa Prize.

Selected experience

  1. 2025–present Co-Founder, BottleCap AI. Founded with Tomas Mikolov and Jaroslav Beck. We raised a $7.5M seed round led by 20VC and are building efficiency-first language models.
  2. 2025 Visiting researcher, National University of Singapore. Worked with Prof. Michael Shieh on Thinking Tokens for LLM reasoning.
  3. 2024–present Co-Founder, Hive Spirit Technologies. Built language-model-driven algorithmic trading systems with Tomas Mikolov for stock markets.
  4. 2022–2025 PhD research, CTU/CIIRC. Research on language models under Tomas Mikolov. First-author papers at ICLR, ECAI and ALIFE.
  5. 2022–2023 Amazon Alexa Prize finalist, Alquist AI. Built open-domain conversational AI for the Socialbot Grand Challenge 5; the team reached the finals and placed 3rd.

Talks, interviews & press

Notable Publications & Releases

ThinkingCap launch graphic
ThinkingCap-Qwen3.6-27B BottleCap AI Open-weights model series, July 2026. Apache 2.0. Qwen3.6-27B with 2× fewer thinking tokens on average and up to 10× faster generation on individual examples, at the same accuracy. Half a million downloads on Hugging Face in its first day; over a million to date across official and community builds.
AI Scan: AI models have hidden preferences. See inside.
AI Scan BottleCap AI Web tool, April 2026. AI contains invisible modifications. AI Scan reveals them: opinion steering, topic avoidance and sensitivity filters, measured on 500,000+ test questions across GPT, Gemini, Grok, DeepSeek and open models.
Diagram from Collapse of self-trained language models
Collapse of self-trained language models David Herel and Tomas Mikolov ICLR 2024 Tiny Papers, Notable.
Alquist 5.0: Dialogue Trees Meet Generative Models. A Novel Approach for Enhancing SocialBot Conversations Ondrej Kobza, Jan Cuhel, Tommaso Gargiani, David Herel, Petr Marek, Jan Pichl, Jakub Konrad, Petr Lorenc and Jan Sedivy Amazon Science 2023.
On Difficulties of Attention Factorization through Shared Memory Uladzislau Yorsh, Martin Holeňa, Ondřej Bojar, David Herel ICLR 2023.
Preserving Semantics in Textual Adversarial Attacks David Herel and Hugo Cisneros and Tomas Mikolov ECAI 2023.
Thinking Tokens for Language Modeling David Herel and Tomas Mikolov AITP 2023.
Emergence of Novelty in Evolutionary Algorithms David Herel and Dominika Zogatova and Matej Kripner and Tomas Mikolov ALIFE 2022.