Lossfunk
We're a lab based in Bangalore, India focused on foundational questions on artificial and biological intelligences. Read our charter to learn more.
Programs
- Research Fellowship (for pre-doc and post-docs): 1 year full time fellowship based out of Bangalore
- Research Internship (for students): 3 to 6 months internship for undergraduate and graduate students interested in AI research
- Residency (for curious minds): a 6 week, on-site, curiosity-led exploration into AI and related topics
Lab's focus
We define intelligent systems as those that achieve their goals successfully, even in situations that they haven’t encountered before. At Lossfunk, we want to study how intelligence manifests in biological systems and then use that inspiration to build artificial systems that go beyond where current AIs are.
This manifests for us in (broadly) three directions:
- AI that adapts to a domain: continual learning, memory, test time adaptation, active learning, sample efficiency, efficient training or inference, personalization, curiosity, exploration, agency, autonomy, OOD generalization, curriculum learning, meta-learning, uncertainty modeling
- Creativity in artificial systems: novelty, creativity, representations, data manifold, extrapolation, surprise, world models, recombination, concept modeling, scientific theory building, innovation, abstractions, program synthesis, knowledge representation, taste
- Biological foundations of intelligence: consciousness, predictive processing, evolution, multi-agents, artificial life, language (origins), developmental cognition, neuroscience, representations, anthropology
Check out this document for a detailed description of our research focus areas.
Papers
Here's a selection of papers from our lab:
- World Models • Hybrid Neural World Models [Preprint] • (website, code, dataset)
- Philosophy • Metaphysical Concepts Should Be Judged by Consequences [⭐ ICML 2026 - main conference]
- RL • Discovering Reinforcement Learning Interfaces with Large Language Models [⭐ Reinforcement Learning Conference (RLC) 2026 - main] • (website, code)
- Consciousness • AI Consciousness Requires Validated Models of Human Consciousness [AAAI 2026 Symposium on Machine Consciousness] • (mirror)
- LLMs • EsoLang-Bench: Evaluating Genuine Reasoning in Large Language Models via Esoteric Programming Languages [Logical Reasoning and ICBINB workshops at ICLR, 2026] • (website, code, dataset)
- AI for science • Why LLMs Aren't Scientists Yet: Lessons from Four Autonomous Research Attempts [Arxiv preprint, 2026] (website, ai written paper, prompts)
- LLMs • Think Just Enough: Sequence-Level Entropy as a Confidence Signal for LLM Reasoning [Foundations of Reasoning Models Workshop at NeurIPS, 2025]
- LLMs • IPO: Your Language Model is Secretly a Preference Classifier [⭐ ACL 2025 - main conference] • (code)
Check out all our published papers (chronologically listed).
Talks
We regularly host talks on AI and related topics at our office in Bangalore and online.
You can access our past talks on our YouTube channel
Stay in Touch
🔔 To get notified about upcoming talks or published papers, join our Whatsapp community (we post ~1x/week)
Links
About
Hi! I'm Paras, founder of Lossfunk. I'm a newly-minted AI researcher [my Google Scholar profile] and a builder [my GitHub profile].
Previously, I founded Wingify, bootstrapped it to $50mn ARR and then exited to a private equity group.
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Stay curious :)
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^^^ World #25 player in chess
