' Hey, Linas here! Welcome back to a ' weekly free edition ' of my daily newsletter. Each day, I focus on 3 stories that are making a difference in the financial technology space. Coupled with things worth watching & most important money movements, it's the only newsletter you need for all things when Finance meets Tech. How to Build an AI Monopoly: The New Rules of Startup Strategy ' [Anyone can build an AI product now. Almost no one can build an AI company. Here is how to escape competition, build moats that compound, and capture the value you create] The Ultimate Guide to Kimi K3 ' [Moonshot's 2.8T open model is now #1 in the world for frontend coding and AI agents at a third of Claude's price. What it changes for founders, builders, and investors, and exactly how to operate it] DeepSeek's leaked investor call: inside the AI Playbook that erased $589 billion of Nvidia's value ' [Liang Wenfeng walks investors through DeepSeek's 6x pricing rule, its 20,000-GPU fleet, the Huawei plan to break CUDA, and an AGI roadmap with dates attached]...

' Hey, Linas here! Every day, I break down 3 stories shaping the future of FinTech & Artificial Intelligence - plus the money movements and trends worth tracking. First time here' 397k+ FinTech and AI leaders get this daily. Join them: Liang Wenfeng has given roughly two interviews in his life. So when a 3-hour-44-minute recording of DeepSeek's founder walking his new shareholders through the entire playbook (pricing math, GPU counts, the Huawei bet, a step-by-step AGI roadmap) leaked out of a May 20, 2026 closed-door meeting, it instantly became the most complete picture available of the AI lab that erased $589 billion of Nvidia's NVDA 0.00%' market value in a single trading day in January 2025. The meeting was Liang's debrief for the incoming investors in DeepSeek's first external financing ever: roughly '50 billion (~$7.4 billion) at a post-money valuation of about $52 billion, per a regulatory filing surfaced by Caixin, from Tencent, CATL, JD.com and NetEase, with Liang personally putting in around '20 billion (~$3 billion) of his own money. Within weeks, a follow-on round was reportedly in early talks at around $70 billion '...

Artificial intelligence is rewriting the world, and simultaneously inventing a whole new language to describe how it's doing it. Sit in on any product meeting, pitch, or panel these days, and you'll hear people toss around LLMs, RAG, RLHF, and a dozen other terms that can make even very smart people in the tech world feel a little insecure. This glossary is our attempt to fix that: pain-English definitions of the AI terms you're most likely to actually run into, whether you're building with this stuff, investing in it, or just trying to keep up by reading TechCrunch or listening to related podcasts. We update it regularly as the field evolves, so consider it a living document, much like the AI systems it describes. Artificial general intelligence, or AGI, is a nebulous term. But it generally refers to AI that's more capable than the average human at many, if not most, tasks. OpenAI CEO Sam Altman once described AGI as the 'equivalent of a median human that you could hire as a co-worker.' Meanwhile, OpenAI's charter defines AGI as 'highly autonomous systems that outperform humans at most economically valuable work.' Google DeepMind's understanding differs slightly from these two definitions; the lab views AGI as 'AI that's at least as capable as humans at most cognitive tasks.' Confused' Not to worry ' so are experts at the forefront of AI research....

Artificial intelligence is rewriting the world, and simultaneously inventing a whole new language to describe how it's doing it. Sit in on any product meeting, pitch, or panel these days, and you'll hear people toss around LLMs, RAG, RLHF, and a dozen other terms that can make even very smart people in the tech world feel a little insecure. This glossary is our attempt to fix that: pain-English definitions of the AI terms you're most likely to actually run into, whether you're building with this stuff, investing in it, or just trying to keep up by reading TechCrunch or listening to related podcasts. We update it regularly as the field evolves, so consider it a living document, much like the AI systems it describes. Artificial general intelligence, or AGI, is a nebulous term. But it generally refers to AI that's more capable than the average human at many, if not most, tasks. OpenAI CEO Sam Altman once described AGI as the 'equivalent of a median human that you could hire as a co-worker.' Meanwhile, OpenAI's charter defines AGI as 'highly autonomous systems that outperform humans at most economically valuable work.' Google DeepMind's understanding differs slightly from these two definitions; the lab views AGI as 'AI that's at least as capable as humans at most cognitive tasks.' Confused' Not to worry ' so are experts at the forefront of AI research....