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reine hassani

T2 · manager / operator

Reine Hassani is the CEO of Liquid AI, a foundation model lab developing post-transformer architectures inspired by C. elegans neural dynamics. He completed his PhD at MIT under Daniela Rus, co-invented liquid neural networks, and leads commercialization with Mercedes, Shopify, and AMD partnerships.

3 calls·3 names·100% bull·last heard 2 months ago·Peter H. Diamandis
track record

no scored calls yet — needs a stated position or a categorical verdict, with a matured window vs SPY

top calls

highest conviction · one per company
1sthigh conviction
$LIQUID-AILiquid AIposition

Liquid AI CEO details post-transformer architecture for efficient on-device SLMs

Liquid AI's neuromorphic-inspired architecture delivers frontier-level intelligence at 10-1000x smaller model sizes, enabling private, offline, low-power inference on edge devices like cars and PCs, with a B2B platform model selling customizable models plus fine-tuning infrastructure.

Peter H. Diamandis2026-07episode →
2ndhigh conviction
$MBGAFMercedes-Benz Group

Mercedes-Benz deploys Liquid AI sub-1GB multimodal model across 2022+ North America fleet via OTA

Mercedes integrates Liquid AI's <1GB multimodal SLM into vehicles (2022+ models) via 600MB OTA update, enabling offline, private, full-car-function voice control with 700-1200 function calls, validating on-device SLM commercial readiness.

Peter H. Diamandis2026-07episode →
3rdhigh conviction
$SHOPShopify

Shopify runs Liquid AI models in production at 1B+ requests, 100M+ users, 10B products

Shopify has deployed Liquid AI foundation models in production for 6 months, serving hundreds of millions of users and 10B products, demonstrating enterprise-grade reliability of non-transformer architectures at massive scale.

Peter H. Diamandis2026-07episode →

most discussed · click a bar to filter

  • $MBGAF
  • $SHOP
  • $LIQUID-AI

recurring themes

  • AI Infrastructure1
  • Enterprise AI Adoption1
  • AI Economics & Business Models1
  • Cybersecurity1
  • Semiconductors1
3 total
$MBGAF
···
Mercedes-Benz Group
HIGHreine hassani·Peter H. Diamandis·2 months ago·Mira Murati's Open Model, Liquid AI's Mercedes Deal, and Meta Gives 3.5B People a Doctor | EP #271
Mercedes-Benz deploys Liquid AI sub-1GB multimodal model across 2022+ North America fleet via OTA
Mercedes integrates Liquid AI's <1GB multimodal SLM into vehicles (2022+ models) via 600MB OTA update, enabling offline, private, full-car-function voice control with 700-1200 function calls, validating on-device SLM commercial readiness.
"We announced the Mercedes partnership as a first uh f first kind of uh point of entry because automotive is like it's very sensitive kind of uh topic and and they're they're prett…"
82:50
$SHOP
···
Shopify
HIGHreine hassani·Peter H. Diamandis·2 months ago·Mira Murati's Open Model, Liquid AI's Mercedes Deal, and Meta Gives 3.5B People a Doctor | EP #271
Shopify runs Liquid AI models in production at 1B+ requests, 100M+ users, 10B products
Shopify has deployed Liquid AI foundation models in production for 6 months, serving hundreds of millions of users and 10B products, demonstrating enterprise-grade reliability of non-transformer architectures at massive scale.
"We recently with with Shopify we entered like uh one uh 1 billion kind of request address inside the Shopify kind of framework And uh there like what we've done we uh we deploy ou…"
91:11
$LIQUID-AI
Liquid AI
HIGHreine hassani·Peter H. Diamandis·2 months ago·Mira Murati's Open Model, Liquid AI's Mercedes Deal, and Meta Gives 3.5B People a Doctor | EP #271· position
Liquid AI CEO details post-transformer architecture for efficient on-device SLMs
Liquid AI's neuromorphic-inspired architecture delivers frontier-level intelligence at 10-1000x smaller model sizes, enabling private, offline, low-power inference on edge devices like cars and PCs, with a B2B platform model selling customizable models plus fine-tuning infrastructure.
"Our mission has always been building efficient general purpose AI at every scale that explores the computational graphs of intelligence beyond transformer and then figure out what…"
7:12
9
AI Infrastructuretailwind
Liquid AI's post-transformer architecture enables frontier intelligence on CPUs at 10-1000x efficiency
Liquid AI's neuromorphic-inspired continuous-time RNN architecture, discovered via automated architecture search (STAR/AFMD), delivers comparable intelligence to transformers at drastically lower memory, compute, and latency, enabling on-device deployment in cars, PCs, and robots without data center connectivity.
8
Enterprise AI Adoptiontailwind
Shopify and Mercedes prove non-transformer SLMs ready for billion-scale production workloads
Liquid AI models serve 1B+ requests/month at Shopify (100M users, 10B products) and power Mercedes' 700-1200 vehicle functions offline; enterprises prioritize data privacy, adaptability, and OTA update efficiency over raw benchmark scores, favoring specialized SLMs.
7
AI Economics & Business Modelstailwind
Fine-tuning as a service emerges as viable model for open-weight labs; customization beats raw benchmarks
Thinking Machines Labs and Liquid AI both pursue enterprise B2B models selling customizable base models plus fine-tuning platforms (Model+X), leaving headroom for customer specialization; OpenAI's fine-tuning API shutdown suggests closed labs abandon this revenue line, creating opening for open-weight specialists.
7
Cybersecurityrisk
Recursive self-improvement enables novel cyber threats; enterprises demand on-prem model control
Liquid AI CEO confirms cyber security threats emerging from recursive self-improvement pipelines (reward hacking, capability emergence); enterprises in defense, banking, and biotech require on-premise fine-tuning to prevent proprietary data leakage to foundation model APIs.
7
Semiconductorstailwind
On-device AI drives demand for efficient edge chips; Qualcomm, Samsung, AMD partner with SLM providers
Automotive and PC OEMs require sub-1GB models running on 2-8GB RAM chips (Qualcomm/Samsung ~$60) with NPU/ASIC acceleration; Liquid AI's AMD partnership and Mercedes deployment validate a growing edge inference market distinct from data center GPU scaling.