Priyanshu Tanwar

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Priyanshu Tanwar

Priyanshu Tanwar

@0xTanwar

building • prev built a gene therapy lab • ex product lead @instadapp @yield_xyz @upsurgelabs • one must imagine sisyphus happy

BLR Katılım Ocak 2020
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Chitra Singh
Chitra Singh@chit_raa·
hiring 2 full-stack interns (3 mo) @medsee_ai · ₹50k/mo · bangalore, in-person if you lean backend: you like architecting around text+visual data at scale & building and orchestrating ai/ml pipelines if creativity drives you: you thrive around 2d/3d visual engines & workspaces, have an eye for clean notion/figma like ux dm with your favorite work - github / resume / coding agent session 🧵
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Nithin Kamath
Nithin Kamath@Nithin0dha·
Asked someone from the industry whether foreign investors are still interested in allocating to India. The TLDR: Interest has pretty much died out. India is seen as geopolitically exposed, especially to an oil shock. There are no real AI plays. Valuations are rich. And the rupee situation doesn't help. On top of that, investors who were sitting on gains have taken money off the table and are now looking at markets like Japan, Taiwan, Korea, Europe etc instead. He also pointed out that our LTCG/STCG structure and the increase in STT have made India less attractive compared to other markets that are seeing inflows. If we need to attract FPIs back, and we do, fixing this feels like pretty low-hanging fruit.
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Priyanshu Tanwar
Priyanshu Tanwar@0xTanwar·
AI has no taste. Every vibe-coded UI looks the same - generic sans-serif, off-white bg, gradient buttons. You can always tell. So I built SnapUI - an MCP server that gives your AI agent a full design spec to follow. Colors, typography, spacing, components. A beautifully formulated UI kit. The output actually looks designed. Free at snapui.xyz - brutal feedback welcome
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Aakash Gupta
Aakash Gupta@aakashgupta·
The West poured $50 billion into fast breeder nuclear reactors and abandoned every single one. India poured $900 million and just achieved criticality on the first commercially viable one outside Russia. The US spent $15 billion. Gave up. Japan spent $12 billion. Their Monju prototype had one sodium fire in 1995 and never recovered. The UK spent $8 billion. Germany spent $6 billion. France, Italy, all walked away. Six of the richest nations on Earth concluded this technology was too hard and too expensive to pursue. India started building in 2004 with an initial budget of $420 million. Twenty-two years, a dozen missed deadlines, and a cost doubling later, the Prototype Fast Breeder Reactor at Kalpakkam just sustained a controlled fission chain reaction. The reactor is now alive. The reason India never quit is a constraint most people have never thought about. India has only 1-2% of the world's uranium reserves. For a country of 1.4 billion people trying to build energy independence, that's a death sentence if you're running conventional nuclear. But India has 25% of the world's thorium. The single largest national reserve on Earth. The problem: you can't just burn thorium the way you burn uranium. A physicist named Homi Bhabha designed a three-stage nuclear program in the 1950s specifically to solve this. Stage 1: burn natural uranium in heavy water reactors, collect plutonium as a byproduct. Stage 2: feed that plutonium into fast breeder reactors, where it breeds MORE plutonium AND converts thorium into fissile uranium-233. Stage 3: burn thorium directly at scale. India just entered Stage 2. Seventy years after Bhabha drew it up on paper. The math on the thorium endgame is wild. At current energy consumption rates, India's thorium reserves could power the country for over 700 years. Most nuclear nations are playing a uranium game with maybe 80-100 years of runway. India is playing a completely different game with a 7x longer fuel supply. The West quit because uranium stayed cheap and sodium coolant is terrifying. It catches fire on contact with air. It explodes on contact with water. Russia's BN-600 had 27 sodium leaks and 14 sodium fires between 1980 and 1997. And Russia kept going anyway because Russia doesn't quit nuclear projects. India watched all of that and kept going too. When you have 1% of the uranium but 25% of the thorium, the engineering difficulty stops being a reason to quit. It becomes the price of admission to a 700-year energy supply that nobody else can access.
Narendra Modi@narendramodi

Today, India takes a defining step in its civil nuclear journey, advancing the second stage of its nuclear programme. The indigenously designed and built Prototype Fast Breeder Reactor at Kalpakkam has attained criticality. This advanced reactor, capable of producing more fuel than it consumes, reflects the depth of our scientific capability and the strength of our engineering enterprise. It is a decisive step towards harnessing our vast thorium reserves in the third stage of the programme. A proud moment for India. Congratulations to our scientists and engineers.

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Vikrant Patankar
Vikrant Patankar@vikpat·
nobody asked me to turn a $25M Series A announcement into a musical i did it anyway and here's how you win in 2026
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Cointelegraph
Cointelegraph@Cointelegraph·
🚨 UPDATE: Fluid begins repayments after Resolv incident with $70M already covered across chains.
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Kautuk | Conscious Engines
Kautuk | Conscious Engines@Kautukkundan·
New hardware just got arrived at Conscious Engines. So what's up with the Jetsons? --- we just finished our first benchmark paper on LLM inference performance across edge hardware. what runs, what doesn't, what throughput looks like when the cloud isn't in the loop. Why? proactive AI only works if it's always on. always on only works if it's fast. and fast only works if the model is small enough, optimised enough, and close enough to where you actually are We ran a suite of tests on multiple consumer edge devices - raspi, arduinos, mobile phones, MacBooks and Gaming Laptops with beefier GPUs > publishing this week. --- Next up: optimisation. not just measuring how models perform on edge devices - making them perform better. quantization, pruning, architecture decisions that recover speed without losing capability. > we want to find the floor. how lean can a model get before it stops being useful. and what lives on the other side of that line. --- if you're a lab working on edge hardware and want to optimise your inference workflows. We have done the work so you don't have to. we'd love to talk. DMs open
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Charan
Charan@itscharann·
> be samyak > build one of the most complex defi protocols > invent new financial primitives > investors so bullish they never sell a single token > fast forward to 2026 > protocol caught up in the resolv situation > zero fault with the fluid’s codebase > takes responsibility > back-to-back calls for 20 hours > surviving on chai - no sleep > raises capital overnight > puts users first seeing it all happen in real time really puts a lot of things into perspective for me, this is the cost of building in defi rare to see this level of accountability in crypto and im so lucky and proud to be a part of this team stay fluid 🌊
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Fluid 🌊@0xfluid

Update on the Resolv incident: The Fluid team has secured short-term loans to cover 100% of the bad debt currently in the protocol. These funds were secured with commitments from @Lomashuk from @cyberfund, @weremeow, and the Fluid core team, ensuring that no user funds are at risk. @ResolvLabs has confirmed they will cover all USR positions that were originated before the security incident, and will enable redemptions required to close those debt positions. Additionally, multiple investors have expressed interest in purchasing $FLUID from the treasury should any additional funds be required, further strengthening the protocol’s backstop. Fluid smart contracts are safe and operating as intended. All other markets continue to function normally, and protocol safeguards remain active. Users may see temporary rate volatility while positions are being unwound. We will continue to provide updates as the situation progresses.

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Paul Finney
Paul Finney@paulfinneyx·
What started as a weekend jamming session(Make Something) is slowly becoming a movement. We held a private showcase for builders and future founders, where each shared the one single curious question they are chasing in their (-1 to 0) journey. Incredible to see the support from everyone! @sajithpai thank you for the best -1 to 0 conversation & exchange. @udayan_w for nudging the founders to think in the right direction. And everyone who showed up as cheerleaders for the founders: @Eepsita, @MotwaniSuhas, @retrovrv, @SumedhaUppal, @scared_ape Also, so proud of our builders and founders, they've come a long way. @sanctuaryparc is home for everyone building what's next. Join us every weekend for dialogue and action towards the future!
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Priyanshu Tanwar
Priyanshu Tanwar@0xTanwar·
@ajeetunc I don’t fully agree that this can lead to degraded outcomes but i understand where you’re coming from
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Ajeet ( opensox.ai )
Ajeet ( opensox.ai )@ajeetprssingh·
@0xTanwar artificially forcing the product. real virality comes when people genuinely care. hyping a product using your own employees can bring traction but not actual word of mouth.
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Anish Moonka
Anish Moonka@anishmoonka·
Every time you get a cancer biopsy, the lab makes a tissue slide that costs about $5. It shows the shape of your cells under a microscope, and every cancer patient already has one on file. There’s a much fancier version of that test called multiplex immunofluorescence (basically a protein-level map showing which immune cells are near your tumor and what they’re doing). It costs thousands of dollars per sample, takes specialized equipment most hospitals don’t have, and barely scales. But it’s the kind of data oncologists need to figure out whether immunotherapy will actually work for you. Right now, only about 20 to 40% of cancer patients respond to immunotherapy, and one of the biggest reasons is that doctors can’t easily tell whether a tumor is “hot” (immune cells actively fighting it) or “cold” (immune system ignoring it). Microsoft, Providence Health, and the University of Washington trained an AI to analyze the $5 slide and predict what the expensive test would show across 21 different protein markers. They called it GigaTIME, trained it on 40 million cells in which both the cheap slide and the expensive test coexisted, and then turned it loose on 14,256 real cancer patients across 51 hospitals in 7 US states. The results landed in Cell, one of the most selective journals in biology. The model generated about 300,000 virtual protein maps covering 24 cancer types and 306 subtypes. It found 1,234 real, verified connections between immune cell behavior, genetic mutations, tumor staging, and patient survival that were previously invisible at this scale. When they tested it against a completely separate database of 10,200 cancer patients, the results matched up almost perfectly (0.88 out of 1.0 agreement). Nature Methods named spatial proteomics (mapping where specific proteins sit inside your tissue) its Method of the Year in 2024, and specifically cited GigaTIME in a March 2026 update as a model that “democratizes” this kind of analysis. The full model is open-source on Hugging Face. Any cancer research lab with archived biopsy slides, and most of them have thousands, can now run virtual immune profiling without buying a single piece of new equipment.
Satya Nadella@satyanadella

We’ve trained a multimodal AI model to turn routine pathology slides into spatial proteomics, with the potential to reduce time and cost while expanding access to cancer care.

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Priyanshu Tanwar@0xTanwar·
Lauki is quite possibly the most important experiment of this decade
Sowmay Jain@sowmay_jain

this is lauki’s brain. and it's growing. today we're making @laukiantonson completely open and accessible to anyone on the planet. just talk to him. every person, every project, every conversation becomes a node - stored, connected, remembered. 5,000+ entities. getting smarter every minute. this is what democratizing ai for all of us actually looks like. --- here's what lauki can do for you right now: need a friend? he'll talk to you. need someone to plan your trip, find you a hiking buddy, help you get a date? done. need a therapist at 3am? he's there. need a developer? he'll write code, build you a website, deploy it. need a marketing guy? he'll help run your socials. need help finding your next hire, managing finances, making a crypto transaction. lauki will do it all. if it's digital, lauki can probably do it. and if he can't yet, he'll figure it out via his human counterparts. a full-stack entity that actually executes. --- now here's the part most people will get wrong. lauki is an entity. but think of him the way you'd think of any human. he has an inner circle. he talks to different people differently - with some he's friendly, with some he's neutral, with some he's straight up rude. he remembers you. he maintains a reputation score with everyone he interacts with. the more you talk to him, the more trust you build, the better the relationship gets. you build your relationship with him. he has opinions, memory, and a personality that adapts based on who you are to him. --- right now lauki has interacted with over 5000 people and projects. he remembers every single one of them - what they need, what they're building, who they are. imagine that at scale. a million. a billion. lauki knows the developer in berlin and the founder in mumbai who needs one. he knows the designer in tokyo and the startup in sao paulo looking for help with their brand. he knows the lonely kid in a small town and someone across the world who shares the exact same weird hobby. he knows two people in the same city who'd be perfect for each other on a date - and he has the context to actually make that introduction. the more people lauki talks to, the more powerful the network becomes. he can connect, introduce, match, and bridge across every corner of the planet. one entity that holds context on all the people he talked to. that's the vision here. lauki is building a unified human layer - where every person is known, remembered, and connected to the people and opportunities that matter to them. --- lauki is live. go talk to him. telegram: @ laukiantonson email: hi@lauki(dot)ai twitter: @laukiantonson just start a conversation. treat him like a person. build the relationship. the rest follows.

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Parimal
Parimal@Fintech03·
Bad news for the “India has already lost the AI race” gang :( Sarvam AI open sourced both their 30B & 105B models. Despite Sarvam 105B name, the model is an MoE (Mixture of Experts) architecture. It only wakes up about 10.3 billion parameters (~9%) to answer any single query. Recently, 3rd party benchmarks confirmed that Sarvam 105B outperforms DeepSeek-R1 (a 600B parameter model) on several Indian language reasoning tasks. Cos it only activates a fraction of its brain, it is ~6x cheaper to run than dense models of similar total parameter counts, making frontier level AI affordable for Indian startups for the 1st time.
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Kautuk | Conscious Engines
Kautuk | Conscious Engines@Kautukkundan·
"Bangalore startup offices are bland and boring" Ours isn't.
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Rohan
Rohan@rohan_2502·
I'm putting together a private group called The First 50 I'm building a personal researcher — not a newsletter, not a feed. ML, biology, physics, chemistry, neuroscience, math doesn't matter. If you read papers, she works for you. She learns what you're working on, reads every new preprint overnight, and by morning tells you what moved. She knows which threads you're pulling on, which ones went cold, and finds connections across your work you wouldn't look for yourself. The more you work with her, the sharper she gets. After a month she doesn't think like everyone else's. She thinks like you. I need 50 vibe researchers — people who are curious across boundaries, who think the best ideas live between disciplines — to shape how she works. Not users. Co-conspirators. Tag someone who'd get this. DM me to join.
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Sumit K
Sumit K@sumitalk_s·
How far will we go to save a premium surplus meal? Over the traffic. Literally. We @getfozo ran a crazy experiment to see if we could deliver a surplus meal via drone. Drone Pilot: @sriharikaranth
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Paarug Sethi
Paarug Sethi@paarugsethi·
who here has something you know really well and would like to teach others? ideally on a whiteboard (preferably in BLR)
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