Srikrishna Swaminathan (@swamikrish2001) header
Srikrishna Swaminathan (@swamikrish2001) profile picture

Co-Founder @Factorsai, disrupting ABM with AI. Formerly leadership @inmobi and interested in startups, marketing, AI, history & Pickleball. Vidya Mandir alum

Bengaluru
Joined November 2009
Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)Photo by Srikrishna Swaminathan (@swamikrish2001)
Srikrishna Swaminathan retweeted
Backflips today, breakthroughs tomorrow. No cap!
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Srikrishna Swaminathan retweeted
🚨Freshworks crosses $1 billion in ARR; Q3 revenue up 14% to $245.4 million Freshworks also said it crossed $1 billion in annual recurring revenue (ARR) after the end of the third quarter, reaching the milestone ahead of its earlier projection of year-end 2026. By @tsuvik moneycontrol.com/technology/…
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Srikrishna Swaminathan retweeted
Replying to @heyshrutimishra
LLMs accumulate a lot of declarative knowledge. That's how they can answer a large number of questions. That's also why they require so many parameters and hence so much memory. But one can replace the accumulation of knowledge by *understanding* That what JEPA world models do. That's one reason they can be useful with considerably less memory and training data than LLMs. This paper merely shows that the underlying similarity structure of the data, whether text or image (e.g. co-occurence of words in text or objects in images) uniquely determines the shape of the representation point cloud, when the encoder is trained trained with a common anti-collapse criterion like SIGReg or VCReg (not by reconstruction).
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Srikrishna Swaminathan retweeted
SaaS bundled software building, hosting, maintenance, security and uptime into one subscription. Vibe coding unbundles the building part. Everything else still needs an owner. “I can build this myself” just created demand for “someone else keep it running.” Maintenance as a service.
i have no time to maintain all my vibe coded tools we need a business model where someone else maintains the code and i just pay a monthly fee
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Srikrishna Swaminathan retweeted
Kalshi just raised an additional $1B, valuing the company at $40B. This will help us expand into stocks, compute, indices, and institutional. Tomorrow marks 8 years since we got accepted into YC and the journey began. The odds of a kid from Lebanon getting here were pretty low. Growing up there was great, but very challenging. We went through war. We had bombs explode in front of my house. I watched brilliant people’s lives destroyed for reasons beyond their control. Lebanon is an unpredictable country. That unpredictability made it hard to plan for success. And yet despite it all, my mom sacrificed everything to give me and my brother the chance to go back to the US. I found my refuge in two things: anime and math. Especially math. I loved math because it calmed me. It was the opposite of unpredictable: clear, deterministic, orderly, and consistent. The proof is either right or wrong. I find that elegant and beautiful. I was lucky. I made it to my dream school, MIT (largely thanks to my mom), and my love for math quickly translated to a love for statistics, probability, and markets. I love markets for a lot of the same reasons. Their incentives are clear: you get rewarded for being right and for pursuing knowledge. They are effective weighting machines for people’s opinions. They provide an incentive to be truthful, because they separate good information from bad information. They let people challenge the consensus and be rewarded for being right. IMO, Hayek, Surowiecki, Hanson, Tetlock were the founding fathers of prediction markets. The more I read them, the more obsessed I got with the idea of applying market-based pricing to more things. Markets bring rigor and critical thinking to more questions. And in an increasingly polarized and information-positioned word, I believe we need that more than ever. Markets would also let people predict and manage more things outside of their control. And the world was becoming increasingly more unpredictable, and more like Lebanon, not less. That love for markets got Luana and me to build Kalshi. At first, it was mostly an idea we couldn’t stop talking about. We didn’t have much money. Luana’s sister bought the Kalshi domain name for us (for ~$1.7k). We moved to SF to get started, and embarked on a long, uncertain journey to build a regulated exchange. The paranoia and anxiety from my childhood never left me. Even when things are going well, I think about what could go wrong. When people trust you with their money, that instinct serves a purpose. I wanted us to build something that would hold up under pressure. The first principle we defined at the company: regulatory-first. We worked with regulators for years before we listed a single market. We took every step to do things the right way and always asked for approval before proceeding. It was very hard at times, especially when we were being overtaken by competitors, but we believe doing things the right way matters. Luana and I aren’t the only ones. Our team put years of their lives into something far from certain. That’s especially true of Lior, Brandon, Rainer, Luis, Xavier, and Josef, who stuck with us for years. They believed when there was little to point to. And they stuck with us no matter how long it took. Kalshi is the result of an arduous journey through a long desert where, at times, most people didn’t understand why we were making the walk. Many people still don’t understand what we’re doing and some disagree with us. Markets have historically taken time to be understood and accepted by some. But while not always obvious, their benefits are vast: capital markets help allocate capital and derivative markets help predict and manage uncertainty. I firmly believe in these benefits, and that’s why I am dedicating my life to building this market. Markets have caused issues many times in the past, and they certainly can present harms (manipulation, insiders, and addictive behaviors). These harms are more acute for certain types of markets (sports, short-term options, etc.) than others. It’s why I believe that guardrails need to exist and why we have taken the approach we have taken. We have consistently prioritized thinking critically about the risks and building the appropriate safeguards, sometimes beyond what the regulators require us to do. Many believe more needs to be done, and that’s a conversation I welcome. Over time, I believe more people will see what we see: markets can help us get smarter and manage the future with more rigor, more precision, and more certainty than we have today. To our tens of millions of users: you have made Kalshi bigger than anything Luana and I could have possibly imagined. Thank you for trusting us and thank you for coming along on the journey. I feel a strong responsibility to build a company worthy of that trust. I am so lucky to spend my life building something I love. I hope everyone finds something they care about that much. Something that keeps you curious. Something that pushes you to your limits. Something that may put you at odds with the status quo. Something worth the hard days. For me, it’s still markets. The more I learn, the more I want to understand.
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Srikrishna Swaminathan retweeted
When Bihar set out to spend Rs 500 crore on a new museum, an academic went to court to stop it. A state this poor, he argued, couldn't afford it. This week, that museum was ranked ninth in the world, above New York’s Met and the Louvre. Swarajya walked through it last year.🧵
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Srikrishna Swaminathan retweeted
In case anyone missed this, OpenAI has proved the Kakeya conjecture in all dimensions. Hong Wang got the Fields medal in 2026 for proving the Kakeya conjecture in dimension 3. In fact OpenAI appears to have committed, in mathematics terms, what may be fairly termed a massacre, proving a far stronger result. It has proved the local smoothing conjecture, which sits at the very top of the tower of conjectures as described in the Quanta article in the reply. I am not an expert in this area -- so happy to be corrected -- but the methods appear to be PDE based and basically bypasses a lot of work of the last two decades. This is the equivalent of Arbreans showing up to earth with an everything killer and explaining to us we have been doing warfare all wrong.
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory). AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
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Srikrishna Swaminathan retweeted
Ashlee - I have been a US-India cross-border VC for a decade and a half now. And I totally get the sentiment around the journey of Ather and many such hardware companies that started in the 2010-2020 generation. They truly struggled to raise early-stage capital in India, given VC was concentrating into eCommerce and Fintech in that decade. Even in those years, the likes of Speciale Invest, YourNest, GrowX, Endiya, VentureEast, Blume, as well as Indian arms of global VCs like Accel, did provide early-stage capital to hardware companies, but the quantum was relatively small, hard to access, and at very low valuations (founders from that generation saw insane dilution levels very early). This has dramatically changed now. India has an active base of angels, micro-VCs, homegrown VCs, global VCs, and strategics/ corporate Family Offices who are willing to bet at the pre-seed & seed stage in deeptech/ hardware. Further, the Govt. is now diverting sovereign money to these managers for early-stage deeptech investing, committing ~$12B over the next 6 years via the RDI scheme. Top-tier tech schools like the IITs, IISc, BITS, etc. now have vibrant incubation programs, many of which have also been allocated RDI LP dollars by the govt. with the objective that early-stage tech derisking in deeptech companies can be funded by them. Also, similar to the US for many decades now, India now has many examples of professors and researchers stepping out to start venture-backed companies that leverage their academic work (eg., Prof Satya of IIT Madras with ePlane and Prof Arin of IIT Bombay with Inspecity). However, I do agree that the Indian venture ecosystem at large needs to: (1) Show more courage & patience at the pre-seed stage. (2) Deliver a better experience for founders, both during the investment process as well as in portfolio value creation. (3) Unlock domestic growth-stage capital for deeptech, as the funnel really dries up at Series B and beyond. But taking a step back, the Indian deeptech venture ecosystem has come a long way since 2011 (which is when I entered venture in India), has shown continued progress on every front, and I expect this to continue and, in fact, become faster over the next decade, with geopolitical realignment + India's macroeconomic growth & scale providing tailwinds. PS: As an aside, I run a Solo GP fund called Operators Studio @opsstudiovc here in SF, where, in addition to backing Silicon Valley startups leveraging India, I have also actively invested in India-based deeptech startups that have the ambition and capability to go global. Like you, I am bullish on India deeptech as a decadal venture theme well into the 2030s. Below is a quick snapshot of my India-based deeptech portfolio (all manufacturing locally). I have been a first check Superangel investor in almost every case: 1) Spacetech - @AuleSpace, @AstrophelHQ, @Cosmochute 2) Aerospace - Aspera (from the Hoskote gang), @ParsecAerospace 3) Precision Engineering & Manufacturing - @NaxatraLabs, @Adiabatic_IN 4) Defense-tech - @SharangShakti, @HyprixAviation 5) Materials - CarbonStrong, Planet Material Labs 6) Consumer Hardware - @cradlewise, @BreethrHQ 7) Robotics - @osmosbot 8) Mobility - @Blinqmobility ...and many more in the pipeline for this Fund.
Why are Indian VCs so afraid to take risk and make money? Someone should go to India and take risk and make money. Our story - corememory.com/p/a-new-india…
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Srikrishna Swaminathan retweeted
In 2025, we published a bold proposal to use fusion reactors for gold production. And now we’ve done it: Mercury transmuted into stable gold, using fusion neutrons, at 10x the record set by CERN in 2025. We’ve reduced alchemy to a series of difficult but tractable engineering problems.
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Need to test it on Bellandur lake…
Turns out the future does have flying cars
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Srikrishna Swaminathan retweeted
When the proof of Fermat's last theorem was announced by Wiles in June 1993, newspapers around the world covered it extensively. I was a ten-year-old boy in Calcutta, India, and the story was splashed across my local newspaper. A few months later, I went to a bookshop with my grandfather and bought two popular books that tried to explain what all the excitement was about. Yesterday was the single greatest day of mathematical breakthroughs in history. This is not an exaggeration. In terms the collective significance and depth of the results released, this was at least ten times, perhaps even a hundred times, as momentous as the proof of Fermat's Last Theorem. So where is the media? Where are the headlines, the breathless newsrooms, the door to door conversations? Where is the sense of incredible wonder this moment deserves?
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Srikrishna Swaminathan retweeted
Not anymore
The convergence of the following series is still an open problem in Mathematics
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Insane !
Today, 18 months after launch, our annualized revenue crossed $1 billion. The platform now powers organizations across the Fortune 500. Enterprise adoption has grown 10x since June. More than 30 million people worldwide now use Higgsfield. Thank you to the creators and teams building with us.
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Humans are apologizing for agent responses
We sincerely apologize for our last reply to you - this is not the way we treat our passengers. We understand your frustration in this matter and are doing everything we can to speed up the process. We will get back to you as soon as possible.
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So much to learn in Geography!
A short #Thread of photos that I clicked while flying between #Chennai and #Thiruvananthapuram last friday. There is no better teacher of Geography than a journey.
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Srikrishna Swaminathan retweeted
Khadim’s legacy cannot be told through what he built alone. It lives just as deeply in the people he believed in and the lives he shaped. Every memory, lesson, and story carries a part of who our Co-founder and founding CEO, Khadim Batti was. We want these memories to have a home. We’ve created a space to honor Khadim’s life and legacy, and invite everyone whose life he touched to share their stories and memories here. ❤️ In loving memory of Khadim Batti: whatfix.com/remembering-khad…
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Sama Veda Avani Avittam in Sri Lakshmi temple , Boston. Vathiyar was really surprised that 8 people showed up ! Got up at 5 am, came here at 6:20 and started at 7:20 and finished by 9:30 AM. Good fun…
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Srikrishna Swaminathan retweeted
What makes solving Navier-Stokes important? Fluid dynamics affects more than you realize in your everyday life. This breakthrough — if it is true — gives you: Cheaper, safer flying and driving. Air over a wing or around a car is a Navier-Stokes problem. Better control of that flow means less drag, so planes and trucks burn less fuel, stay quieter, and stall less often. Weather you can actually plan around. Storms, jet streams, and ocean currents are giant fluid problems. Sharper turbulence physics is one of the remaining limits on hurricane tracks, heat waves, and flood forecasts. That is the difference between “maybe evacuate” and a clear warning. Hearts, stents, and artificial valves. Blood is a fluid. Doctors already simulate flow through arteries and implants from CT/MRI scans. A more reliable theory of swirling, high-speed blood flow would help design stents, heart valves, and aneurysm treatments that work better. Cleaner power from wind and turbines. Wind hitting a turbine blade, steam inside a power plant, and fuel mixing in an engine are all the same equations. Better models mean more electricity from the same wind farm and engines that waste less fuel Ships, pipes, and dirty air. Oil in a pipeline, water in city mains, smoke over a city, and waves slamming a hull all follow Navier-Stokes. Better predictions cut leaks, pump energy, and help track pollution after a spill or wildfire. Many other everyday effects: buildings, sports, and rain. The same math decides whether a skyscraper sways in a gale, why a dimpled golf ball flies farther, how air moves through a house’s vents, and even how raindrops form in clouds. Those are not abstract puzzles; they are why planes fly, forecasts exist, and a stadium roof doesn’t peel off. None of this happens instantly because of a math problem solution by AI. But everything that does happen is going to help engineer a better life for all of us. This is big.
Solving Navier-Stokes is a real leap. Out of all the math problems AI has cracked so far, this is the first one that could actually help humanity in practice. Before this, AI was mostly brute-forcing one or two Erdős problems out of 1,200 with raw AI compute, and solving those didn't really change much for the real world. We are accelerating. Get ready to keep up.
Readers added context they thought people might want to know
This result proves Navier-Stokes solutions can develop singularities (break down) in finite time under specific conditions, per the Millennium math problem. It yields no established gains in turbulence prediction, engineering, forecasts or medicine. openai.com/index/navier-s… claymath.org/millennium-pro… physics.stackexchange.com/questions/8756…
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