I help founders, write about AI and share behind-the-scenes lessons from founding https://t.co/JPQUw7ggAp ($150MM+ revenue/year). Raised $150MM in VC. Angel Investor.
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Jan 21 • 11 tweets • 5 min read
DeepSeek just released the first Open Source Reasoning Model that matched o1!
But how did an unknown, 100 person startup with $0 VC funding produce a frontier open source model that rivaled OpenAI and Anthropic at 1/10th of the training cost and is 20-50x cheaper during inference?
After doing extensive research into the company's history, here’s the untold founding story of the rise, fall and rebirth behind DeepSeek and it’s parent company High-Flyer 🧵 1. Humble beginnings
In 2007, three engineers Xu Jin, Zheng Dawei, and Liang Wenfeng (CEO) met at Zhejiang University and bonded over algorithmic trading .
Their idea? Build a quant fund powered by cutting-edge AI. But instead of hiring industry veterans, they prioritized raw talent and curiosity over experience. Liang: “Core technical roles are primarily filled by recent grads or those 1–2 years out.”
Dec 30, 2024 • 9 tweets • 4 min read
In just 2 days, Deepseek v3 became the #1 programming model on @OpenRouterAI, beating Claude 3.5 Sonnet, GPT-4o and capturing over ⅓ of all tokens.
But how did an unknown, 100 person startup with $0 VC funding produce a frontier open source model that rivaled OpenAI and Anthropic at 1/10th of the cost?
Here’s the untold founding story of the rise, fall and rebirth behind @deepseek_ai and it’s parent company High-Flyer 🧵1. Humble beginnings
In 2007, three engineers Xu Jin, Zheng Dawei, and Liang Wenfeng (CEO) met at Zhejiang University and bonded over algorithmic trading .
Their idea? Build a quant fund powered by cutting-edge AI. But instead of hiring industry veterans, they prioritized raw talent and curiosity over experience.
Liang: “Core technical roles are primarily filled by recent grads or those 1–2 years out.”
Jan 29, 2023 • 14 tweets • 3 min read
We at Super successfully transitioned to a fully remote company, hired 100+ people, and raised $100MM+ in a little over 1 year
Here’s how 🧵
Scaling up creates information asymmetry and goes against an open and transparent culture.
This can be reversed if we operationalize the flow of information - which is best achieved by implementing a culture of writing and reading