Sumer Sao

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Sumer Sao

Sumer Sao

@sumersao

meditating to keep my heart rate down so I can drink more coffee // prev @kalshi @robinhoodapp @stanford

San Francisco Katılım Ocak 2021
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Sumer Sao
Sumer Sao@sumersao·
Most successful rebrands in history: War Department -> Dept. of Defense (1947) Global Warming -> Climate Change (2006) ... Cron Job -> AI Agent (2024)
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Sumer Sao
Sumer Sao@sumersao·
🚀🚀 legendary results for a legendary team (130 ppl btw)
Tarek Mansour@mansourtarek_

Kalshi raised $1B at a $22B valuation led by Coatue, with participation from Morgan Stanley, Sequoia, a16z, and others. In 2018, we were two kids who loved math, markets, and debate. And we had a dream: build the next generation financial market, where we capture a broader set of questions and harness the power of the masses to price them better than Wall Street. Kalshi was born to fulfill that dream. Today, most of these questions are traded indirectly, priced through imprecise proxies or negotiated bilaterally in opaque, restricted, relationship-driven markets. But thanks to our incredible community of users who make our markets work, Kalshi has the opportunity to change that by turning historically fragmented and untradeable risk into open, liquid, and standardized markets. We’ve seen this movie before. When interest rates, currencies, commodities, and crypto moved from dark to lit markets, volume did not just migrate: access expanded, new use cases emerged, and the opportunity grew by orders of magnitude. Today, Kalshi represents over 90% of US prediction market volume and the majority of activity globally, with annualized volume growing to $178B over the past 6 months. What started as retail is quickly becoming institutional — hedge funds, asset managers, prop firms, and insurers are beginning to trade, provide liquidity, and hedge real-world risk directly. The scope and scale of prediction markets are just beginning to take shape. We’re using this new capital to accelerate the institutional adoption underway — unlocking trillions in capital to facilitate active trading and risk management. Prediction markets are moving from early adoption to core financial infrastructure. This is just the beginning.

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Mihir Garimella
Mihir Garimella@mgarimella·
📣 We just raised our $45M Series B from @TCVTech and @firstharmonic, with participation from @BainCapVC, @firstround, and @AlkeonCapital. Sales is the most expensive function in most companies — and one of the hardest. Hundreds of accounts, different context, different stakeholders, different dynamics, and a different path to close. No one can do that perfectly. Critical things get missed. So we gave every account its own AI agent — working 24/7, maintaining full context, progressing it through the funnel, and guiding reps and leaders on what to do next. The greatest privilege has been building alongside companies like @Samsara @tryramp @ironclad_inc and @attentiveHQ — enterprises with thousands of sellers who are already living in the future. There are only two unbounded upside problems out there: building and selling. Every company sells. and @useactively is building the system they'll all run on. We’re excited to pull every revenue team into the future we know is inevitable.
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daniel
daniel@DanielEdrisian·
I've left OpenAI and the Codex team to build Blackstar: A new hardware company building the future of human-computer interaction. We believe that software is solved. Building apps is now easy, but the next meaningful improvement in human-AI communication requires changing the OS & hardware. That's why we're building a new device entirely. I'm also excited to announce our $12m seed round led by @AbstractVC, with participation from @naval, @SVAngel, @chapterone, and Timeless, among other amazing angels who've supported us from the old Alex days.
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Sumer Sao
Sumer Sao@sumersao·
@DustinGouker I believe that in the limit self regulation only occurs because of external regulation. I don’t believe in benevolent dictators. Re victory lapping, my only belief is that mistakes are unavoidable, and not making a mistake to begin with should always be the standard!
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Dustin Gouker
Dustin Gouker@DustinGouker·
Kalshi was also promoting betting on the Khamenei market on Saturday despite it not being a “death” market. Glad they did the right thing but the victory lapping of it is weird. Also this was entirely self regulation, which is fine but has nothing to do with actual regulation!
Sumer Sao@sumersao

Mistakes are unavoidable, fixing them correctly isn't. @Kalshi demonstrating once again why regulation is at the core of making prediction markets useful and safe for all.

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Sumer Sao
Sumer Sao@sumersao·
@sean91237 @Kalshi You need both for sure. Benevolent dictators don’t endure, the system needs checks/balances
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Sean
Sean@sean91237·
@sumersao @Kalshi Not a regulation issue. These can be solved internally by having strong processes. CME works well not because of regs but trusts and knowledge built over decades
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Sumer Sao
Sumer Sao@sumersao·
Mistakes are unavoidable, fixing them correctly isn't. @Kalshi demonstrating once again why regulation is at the core of making prediction markets useful and safe for all.
Tarek Mansour@mansourtarek_

As an exchange, we resolve the market according to the rules, even when there is disagreement with the resolution. I understand many of you are frustrated about the Khamenei market, and I want to clear up a few things along with steps we have taken to improve: The market rules were not changed. The death carveout and settlement based on last-traded-price were part of the published market rules from the outset (see the screenshot from the rules, which can also be found in our official filing from 2025 on the CFTC website). The death carveout was also always shown on the market page (see market page below). Once the strikes on Iran started, we added the “Green Box” to further highlight the death carveout in the UI (this is not a rule change, just a highlight of the rules). We settled according to the rules. Traders were paid based on the last traded price. Some traders who held YES feel like they should have won (as in the market should have settled to YES). But the rules clearly stated that the market would not settle to YES in the event of death: traders expect us to settle the market based on the rules and we have to apply the rules consistently for both YES and NO holders; changing settlement because one side is unhappy would break trust in the exchange (imagine you held NO and you read the rules, but then we decided to settle contrary to the rules). Death carveouts are important; as a federally regulated prediction market, we are required and feel it is important not to enable direct profiting from war, assassination, terrorism, or other violent outcomes. No trader lost money on this market. While the rules were clear and we tried our best to highlight them, traders vocalized they were not prominent enough. We heard you, and we decided to reimburse out of pocket for all fees and all net losses from trading in the market: 1. If you sold for a net loss before settlement, we reimbursed you for that net loss and 2. if you didn’t recoup your position cost during settlement, we paid you the difference so you get your full position cost back. You can find reimbursements under "Your activity" in the app and website. No trader ended net-negative after our reimbursements. Kalshi did not profit on this market. We do not stand to benefit from one resolution or the other. We earn fees from facilitating trades. For this market, we reimbursed all fees back to users. We also reimbursed net losses users incurred on the market out of pocket, so no trader ended net negative. As a result, Kalshi incurred a substantial loss to make users whole. We will improve. We learned a lot from this market. We are updating how we present similar markets (e.g., those with a death carveout or where a death might be a likely scenario) so traders can see the exception more clearly before they trade. We will surface the exception in the title and at the top of the market page. We also recognize that the first iteration of the Green Box warning created confusion; we revised it and reimbursed net losses for the market. Going forward, we are implementing a tighter review process for UI highlights. The best part about Kalshi is you all and I'm sorry for the disappointment. We'll improve, thank you for bearing with us.

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Naveen Rao
Naveen Rao@NaveenGRao·
We're proud to announce @unconvAI a bit more publicly! We're in unprecedented times...AI has exponential demand but is limited by (linear) energy build-outs. At Unconventional we're aiming to use every watt more effectively; we're doing it by going to first principles on how to build an intelligence substrate. Biology scale efficiency in 20 years!
Unconventional AI@unconvAI

AI scaling will be energy-limited at the global level in the next 3-4 years. Conventional computing is reaching its limits. It’s time to stop simulating neural networks on digital logic and start building hardware that actually behaves like them. We are Unconventional AI. Learn more about our mission: unconv.ai/introducing-un…

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Sumer Sao
Sumer Sao@sumersao·
@_rainerds the ppl made it worth the pain!! (and late night taco bell)
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rainer 🇭🇹🌹🌱
rainer 🇭🇹🌹🌱@_rainerds·
I have a confession to make. We thought Kalshi would be an instant success. Of course we did; our team was full of evangelists and missionaries who believed in prediction markets. Better yet, Tarek and Luana had already done the hard part: spending two years to get an exchange license. But... we had no exchange. What followed was an eight-month gauntlet of technical challenges, business negotiations, and regulatory whiplash. When we finally launched, we thought we’d made it. But no one cared. This is one of many stories that defines Kalshi. Even through painful, consistent, and creative work, growth was never promised. But the hard times built us up—they taught us how to create from nothing. We fought for every inch of growth and figured out what worked by trying everything that didn't. When no one else wanted to, we built our own clearinghouse, brokerage, and liquidity. We yearned for growth so badly that we risked the company to democratize elections. $11B sounds surreal, but we all knew we'd make it here. And we still have so much more to give. Time to put our money where our mouth is. I like our odds.
Tarek Mansour@mansourtarek_

Kalshi raised $1B at an $11B valuation. A decade ago, only a few thousand people knew what a prediction market was. Eighteen months ago, most prediction markets were banned - until we overcame the government to set them free. Over the past seven years, our community has opened up an entirely new category. Today, Kalshi is trusted, used, and loved by millions of people. It’s a part of everyday culture, and it’s driving one of the most important shifts in consumer behavior in recent history. The time has finally come for prediction markets to achieve their full potential and we are intent on making that happen. To all the believers and the early adopters: thank you.

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Yash Patil
Yash Patil@ypatil125·
Today, @rhythmrg, @lindensli and I are introducing @appliedcompute. We’re building Specific Intelligence for the enterprise. Achieving SOTA today means specialization in both human and machine talent. We’ve spent the last six months working with companies like @cognition, @DoorDash, and @mercor_ai, unlocking their company knowledge to build custom agent workforces that outperform frontier models at specific tasks. My cofounders and I all worked on different parts of this problem while at OpenAI, from Codex to o1 to the ML systems and infrastructure for RL training. Two-thirds of our team (see below!) are former founders, and everyone brings a deep technical background, from top AI researchers to Math Olympiad winners. We’ve raised $80M from @benchmark, @sequoia, @Lux_Capital, @eladgil, @victoralazarte, and @Casspi18, and we’re hiring across engineering and research.
Yash Patil tweet media
Applied Compute@appliedcompute

Generalists are useful, but it’s not enough to be smart. Advances come from specialists, whether human or machine. To have an edge, agents need specific expertise, within specific companies, built on models trained on specific data. We call this Specific Intelligence. It's what we're building at Applied Compute. We unlock the latent knowledge inside a company, use it to train custom models, and deploy an in-house agent workforce that reports to your team. We work with sophisticated companies that have already captured early gains from general models, like @cognition, @DoorDash, and @mercor_ai. They’re pulling even further ahead with proprietary in-house agents that don’t need to wait for the next public model release. Together, we are building and validating models and agents in days instead of months, achieving state-of-the-art performance on customer evals. Our team has high density and low latency. Our founders all worked on different parts of this problem while they were researchers at OpenAI — @ypatil125 as a key member on the agentic software engineer effort (Codex), @rhythmrg as a core contributor to the first RL-trained reasoning model (o1), and @lindensli as a core contributor on ML systems and infrastructure for RL training. Two-thirds of the team are former founders, and everyone brings a deep technical background, from top AI researchers to Math Olympiad winners. We are backed by $80M in funding from Benchmark, Sequoia, Lux, Elad Gil, Victor Lazarte, Omri Casspi, and others. With their support, we are growing the team, scaling deployments, and bringing to market the first generation of agent workforces built on specific models. In short: 1. We are building Specific Intelligence for specific work at specific companies. 2. That will power in-house agent workforces to support their human bosses. 3. That in turn will unlock AI’s full potential through humanity’s greatest engine of progress: thriving corporations in a free market.

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Karan Goel
Karan Goel@krandiash·
We've raised $100M from Kleiner Perkins, Index Ventures, Lightspeed, and NVIDIA. Today we're introducing Sonic-3 - the state-of-the-art model for realtime conversation. What makes Sonic-3 great: - Breakthrough naturalness - laughter and full emotional range - Lightning fast -
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Lotanna Ezeike 💳
Lotanna Ezeike 💳@lottsnomad·
we’re building payroll for the modern workforce & we're raising in SF > gusto built payroll for employees ($9b) > deel built payroll for contractors ($17b) no one has built payroll for performance we’re doing that. starting with pay-per-view - companies want to pay for results, not retainers. YouTube alone has paid out $100B+ based on video performance Successful apps like Cal AI & Quittr are running $500k+ monthly ugc campaigns but its impossible to: > calculate views across platforms > pay people anywhere in the world > stay compliant with taxes and reporting so we fixed it. our platform makes it easy to pay anyone, anywhere, for performance. > ⁠one dashboard > ⁠instant global payouts > ⁠automated compliance no spreadsheets, no stress. - i’ve spent the last few years building, scaling and exiting apps that reached millions of users. i paid hundreds of contractors and creators on a CPM or performance basis. it always felt broken. every week was a mess of spreadsheets, invoices, and late-night Slack messages asking... “how much do we owe Emily this week?” that’s when I realized, the system we needed didn’t exist. so we built it. we started hosting the biggest consumer app events in SF (1000+ people came to my home) on the surface it looked like community building in reality it was market research we wanted to see if others felt the same pain we did they did. it was so painful that when we raised our angel round, a customer invested mid convo (crazy) today we’re launching with $500k in monthly payroll ready to go and another $1.5m in pipeline how? > i run a community of 400+ app founders, scaling through performance based ugc marketing > i've helped marketing agencies close down new clients doing performance based organics > i am the distribution. this isn’t theory it’s real, and it’s live today here’s how we see it: the future of payroll isn’t hourly. it’s not monthly. it’s performance based. You deliver results, you get paid. Simple as that. > Gusto built payroll for jobs. > Deel built payroll for work. > We built payroll for performance. if you're in SF and back early stage founders, i want to meet you
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Sourish Jasti
Sourish Jasti@SourishJasti·
1/ The future of general-purpose robotics will be decided by one major question: which flavor of data scales reasoning? Every major lab represents a different bet. Over the past 3 months, @adam_patni, @vriishin, and I read the core research papers, spoke with staff at the major labs, and mapped the talent pool. This has completely changed how we think about general-purpose robotics. Our paper builds intuition, step-by step, across the 2025 frontier: from architectures → evals → data → industry dynamics. Each layer reveals a different bottleneck, but they all converge on one truth—data decides everything. Our takeaways + process below👇 If you want access to our graph (sound on), comment or DM me
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kayla
kayla@kaylanhua·
Sway: influence elections, the right way. Everyone cares about something. Vote with those who share your values and make it happen.
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surya
surya@suryamidha·
last week, I shared with the mercor team that I’ll be transitioning into a new role as chairman of the board and stepping away from my position as chief operating officer. mercor has been the defining journey of my life. I first met adarsh when I was 10 and brendan when I was 14, back on our high school debate team. years later, after our sophomore year of college, we took a leap of faith and started mercor out of a tiny palo alto office barely larger than a conference room. none of us could have imagined the scale and impact the company would achieve in such a short time. this decision comes from a place of conviction, not doubt. I believe in our mission more deeply than ever and have complete faith in the team to carry mercor into its next chapter.
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Tarek Mansour
Tarek Mansour@mansourtarek_·
Team got us shirts for the occasion.
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