Icons
@sv_icons
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Where the next generation of power is born. Stanford-rooted community of 2,000+ students and alumni changing the world
Stanford, CA
Joined May 2023
Product Cycles > Financial Cycles...and one way to build around the AI Product Cycle: going "greenfield" Below is a chart of the Nasdaq vs the biggest product cycles of the past 45 years: PC, Internet, Cloud, Mobile, and now AI. Each had an infrastructure layer and an
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Let's celebrate this moment of recognition of our community by Stanford. Stanford one love 🥰
Every time we host someone at @sv_icons, I feel one step closer to thinking like our speakers. After hosting 220+ speakers over 4 years, I’ve developed a better sense for what questions spark the most revealing answers. Ultimately, all hosts and members aspire to become icons
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9/12/7 is better than 9/9/6 - Alex is a top performer of SV Icons
Last week we had a chance to host @alexblania , founder of @worldcoin for @sv_icons. Alex studied physics at caltech and then co-founded World and Merge Labs with @sama . Here are a few insights from the conversation: -World rests on three core assumptions: most future
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We started @laborup_usa with a simple belief: America can’t rebuild its industrial base without rebuilding how we hire the people who power it. We raised $7.7M to build the defining AI solution that is Solving America's $1 Trillion Manufacturing Labor Crisis. I sat down with
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We were honored to host @alive_eth, general partner at @a16zcrypto, for our dinner last week. Contrary to popular opinion, Ali thinks that Finance is not the only use case of blockchains - they invert the relationship between hardware & software, creating global public
Last week we were lucky to host @alive_eth for @sv_icons dinner. Ali leads crypto investing at @a16zcrypto , and has been behind some of the fund’s landmark bets, including Solana and LayerZero. His core belief - blockchains aren't just about finance. At their core, blockchains
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It was a pleasure hosting @QwQiao, the founder of @alliancedao, for our dinner at Icons. 1) Founders > ideas. 2) Raise only what you need. 3) Solve the problems you experienced. 4) Privacy is the next big vertical for funding. These and every other insightful take from the
Last week we had a privilege to host @QwQiao for off-the-record @sv_icons dinner. Qiao is the founder of Alliance DAO, the best accelerator for crypto startups. Here's the list of the best takeaways from Qiao: 1. Most customers lie. They’ll tell you they need your
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SV Icons' dinner with @htaneja is the one to remember. Hemant is the CEO of @generalcatalyst and has invested in companies that have transformed industries forever. The three lessons he shared that none of us will forget include: 1) Pattern recognition can kill innovation -
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During his dinner with Icons, @DAlperovitch, the co-founder of one of the most iconic cybersecurity companies, @CrowdStrike, shared his core principle when it comes to choosing the right people to work with: Never settle when it comes to the qualities of your hires.
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The consensus on AGI is that it will leave no jobs for humans; therefore, no purpose to continue living. @kevinweil shared during his dinner with Icons that, contrary to what the masses believe is actually true, AI will reshape the work, not end it. Skeptics outnumber
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Icons hosted a dinner with @erichorvitz, the Chief Scientific Officer at @Microsoft. He's working at the frontier of AI development, and here's one of his core insights about AI and the future of jobs:
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8. FutureHouse's AI discovered a novel treatment for AMD, a major cause of blindness. The entire process, spanning hypothesis generation to data analysis, was carried out by AI, all while remaining open-access and mission-driven as a non-profit organization.
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7. VCs already know what they want. People rarely change their opinions. Trying to convince VC is full BS, you just need to find a VC who already believes that your idea is great, and then you make sure he believes you’re the right founder for the idea
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6. AI enables the combination of knowledge from scientific discoveries across countries, regions, and years. In fact, Future House has referenced scientific papers published in the 1800s.
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5. We won’t solve the aging problem within the next ten years. Proving efficacy alone takes a decade. Most other problems, however, can be solved more quickly.
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4. If you don’t provide the information to LLM on where to look for scientific hypotheses, it will just hallucinate. That’s what LLMs are built to do.
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3. The bulk of upcoming GenAI breakthroughs in science will come from large-scale knowledge processing. Physical experiments are still a bottleneck, and lab automation technologies are more focused on repetitive processes (like an assembly line in a car factory) rather than
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2. If you start a Ph.D. today, be careful. By the time you graduate, AI may already do the thing you planned your thesis around. Aim for problems that will still matter in five years.
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1. AI’s scientific progress is accelerating in unexpected ways. What great minds considered impossible a few years ago is now in production. We are about to witness a tsunami of discoveries and innovations across scientific fields.
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