Vir retweeted
I'm so excited to be releasing this engine.
This represents the first of hopefully a long line of work with Nvidia
We didn't put comparison charts in the main post
but rest assured
WE SMOKED EM
this is the best engine for your dgx station.
its not close.
Actual Computer turns your NVIDIA DGX Station into a department-scale AI factory.
Read the full case study:
actual.inc/company/blog/case…
Vir retweeted
“JP Morgan projects $115B could enter India’s stock market as investors hedge crowded AI exposure. India is emerging as a default safe haven, supported by policy alignment and small- and mid-cap earnings growth.” finance.yahoo.com/markets/st…
The same is true for private capital markets too. India continues to invest in enterprises of diverse industries and scales in private equity and venture capital - the type of investment which will help India to triple its economic output.
India is not a one-sided YOLO AI trade, where 8.8% of GDP needs to be splurged on AI to justify the capital expenditure underway. xitter.cf/rmantri/status/2110039…
Credit markets are signaling what is coming 🚨 xitter.cf/schuldensuehner/status…
The AI infrastructure boom is funded heavily with debt - and borrowers are merrily offering chips as collateral. bloomberg.com/news/articles/…
Some people are comparing India returns to this madness and lamenting the Indian market’s performance.
Be careful of such people. They are the classic late momentum skirt chasers - clueless about what fundamentally drives economic performance (which in turn delivers stock market returns).
We should be glad that India has a diversified economy catering first to India’s needs, and a sound demographic balance that will sustain growth for decades to come.
India is not an economy where 2/3 companies generate all the profits and society is facing a demographic cliff. Or one where state-directed “industrial policy” has a free run to pick winners and crush those who are non-complaint.
Vir retweeted
A company sent an AI recruiter to interview him, so he sent his own AI agent instead
The two AIs discussed the job between themselves. No human was on the call
Then both of them glitched, and got stuck saying goodbye to each other. Endlessly
Job interviews in 2026: your agent talks to their agent, and neither knows how to hang up
Vir retweeted
Deedy you are right about some aspects of the past, but its more nuanced then this, and likely different going forward. am sticking to the perspective of founders (vs employees & vcs).
If you were building for India consumer, the last 5 years have shown that you absolutely could have built significant cos and personal wealth by being in india (>$5b cos - flipkart, zomato, lenskart, meesho, groww, paytm, phonepe, swiggy, policybazaar, nykaa… ) and execs at these places also saw a lot of value being created. I was in a room of startup founders by @ETAwards on friday night and there were a lot of billionaires there! and 50+ other venture backed cos in the $500m-5b range, where also the outcomes have been significant for founders and execs.
if you were building for global software buyers, you need to be closer to the customers and the US is that. market insights matter more then cost of engineering. many global software cos have large india teams (zscaler! wealthiest indian american in the US) but the bulk of the value to founders and execs are in the market they serve. it still makes sense for most global founders to be in the US if thats what you are creating, and we have good examples like freshworks, postman and composio where cos started in india and migrated over various points in the past decade.
other areas like manufacturing/“deeptech”/atoms based businesses, India has significant advantages and we are just starting to see the outcomes. ather energy ($6b), skyroot ($3b), zetwerk (going public soon) are showing the way, and these cos have far lower costs to develop and manufacture vs other places.
finally, there is something to be said for patriotism or impact on soceity. zomato helps employ 1% of india (or something like that) and thats a stepping stone to a brighter future for many. skyroot inspired some young kid somewhere that said i’m gonna do that too. building a enterprise sw product in palo alto is awesome, but for some gives less intrinsic motivation.
building in india has many challenges (most self inclicted), but a good choice for many smart people vs a couple of decades ago! we do now have healthy capital markets, a better policy environment, and very smart young people (now enabled by AI!). we absolutely need more risk capital and some of us are working to do that!
The smartest Indians continue to come to build in the US for the simple reason that the economic incentives are far far better.
Perplexity ($20B), Skild ($14B+), Baseten ($13B), Together ($8B), Glean ($8B), Modal ($5B), Rubrik ($25B), Harness ($5B), Blacksmith, Parallel, Greptile, CodeRabbit, Composio, Distyl ($2B), Resolve, Luma, Cartesia, Wispr, dMatrix, Arize and many more - all started by at least one Indian-born founder.
The US is a far easier to raise capital in with far less dilution. Most Indian companies are switching where they're domiciled to get access to the US capital markets. Every single Indian venture firm is trying very hard to invest in the US or risk not participating in the AI race (ironically, the management fees of venture firms are so high in India relatively that this is the one group that net of carry actually has incentive to be in India because they take home well north of a living wage whether or not funds perform do)
While Zomato ($35B now, $8B at IPO) might be the biggest outcome in Indian venture, Cursor ($60B), Reflection (potentially $20B+), World Labs ($8B), OpenRouter ($8B), HuggingFace ($12B) and of course the $1T+ big labs quickly make those outcomes seem small and happen on a much smaller time scale, with much higher IRR.
Engineers at these startups regularly get paid $1M/yr, and make $10M+ on exit. Even in BigTech, it is trivial to pull up levels fyi and see that if you're L6/L7+ with ~10 years of experience, you're making $1M/yr there too. And of course, we all know the slew of Indian CEOs of companies here, not to mention a huge bench of lesser known executives across the board in public and private companies.
I say all this because every time there is a slight immigration hiccup in the US, I hear the online pleas to "build in India", I struggle to understand why most engineers, academics or founders would do that net of desire to be close to family, failure to obtain visa and devout patriotism.
This is not a superiority thing or a US v India thing. The economic incentives at least for technologists to being in the US outweigh India by at least an order of magnitude.
Vir retweeted
Stop overthinking what stocks to buy
All eyes on SpaceX
Rep. Maria Elvira Salazar (R) just bought up to $30,000 in SpaceX
She's the 7th member of Congress to buy $SPCX since the June IPO
Combined buyers so far: 7
Combined sellers: 0
Vir retweeted
Salesforce acquires Listen Labs for ~$2b. But who gets the 💰? My usual breakdown below 👇
The company was founded in Sep-23 and had raised less than $100m. Investors will share ~$850m of profits on $96m invested, a ~10x blended.
From a huge pivot to a unicorn valuation term sheet they refused, this is truly a wild story ✍️. In the end an incredible outcome for all involved.
So let's dive in!
1) The boldest move: walking away from $1.5b 🎲
Listen Labs had a signed $125m Series C term sheet from Menlo at a $1.5b valuation... and walked away from it to sell to Salesforce at ~$2b.
This takes a huge amount of courage: few founders turn down a signed unicorn-plus round. @itsalfredw and @florian_jue did it 2.5 years after founding.
Huge congratulations are in order for the discipline and execution of the founders here.
2) Founders and team: a life-changing outcome in under 3 years 🥳
By my best estimates, founders and team still own over half the company.
At $2b, that's ~$1.1b for them to share. Specifically, assuming a 15% option pool, that is ~$300m for the team and ~$750m for the two co-founders.
And, as was the case with Hugging Face, this is all from a pivot. They originally built an AI customer-interview tool to understand why their viral app BeFake was growing, then realised the tool was the business!
3) Sequoia's Bryan Schreier did it again 👑
What few people know is that Bryan was an early backer of Qualtrics... the category Listen Labs is disrupting.
Now he led both the seed and the Series A here. By my estimates, those two rounds will return ~$670m combined, or ~25x on ~$27m invested, in under three years.
Pattern recognition and industry knowledge have their perks, it would seem!
4) Ribbit: 4x in 8 months ⚡
Ribbit led the $69m Series B in Jan-26 at ~$500m. At $2b, that's ~4x in 8 months. Unbelievable IRR and a great return on a meaningful cheque.
5) Neo does it again, congrats @apartovi 🎯
Listen Labs went through the Neo accelerator early on, which came with a $600k SAFE. On my estimates, that cheque is worth ~$25m+ today.
This comes just three months after Cursor's acquisition (a cool >1,000x for Neo). What a hit rate!
This one is very straightforward: it is a massive win for everyone. And so congratulations to all involved: Sequoia, Ribbit, Conviction, Pear, Neo and the team!
Vir retweeted
I got updated information on Instinct’s earliest financing and the math is pretty wild.
Confirmed:
Conviction invested $5M at a $50M valuation.
Greenoaks fast followed with $10M at $100M.
Instinct is now reportedly discussing raising another $1B at a ~$10B valuation.
For easy math, assume the first investment was exactly one year ago and 20% dilution every subsequent round with no pro rata.
Conviction:
$5M → ~$512M
102x MOIC
~10,140% IRR
~$507M paper gain
Conviction’s fund is ~$230M, so this one investment alone would be worth ~2.2x the entire fund.
Greenoaks:
$10M → ~$512M
51x MOIC
~5,020% IRR
~$502M paper gain
Funny enough, they end up at basically the same $512M because Greenoaks invested 2x as much at 2x the valuation.
Obviously this is all paper. The $10B round hasn’t closed and none of this is DPI.
But this is why the venture game can look so crazy.
It’s also why making money can sometimes get in the way.
If Instinct can raise another $1B, they can hire whoever they want, pay for the millions they’re likely burning every month on compute and keep growing.
Get distribution. Build something everyone uses. Figure out monetization later.
Most startups don’t have that luxury. But when investors are fighting to give you another billion dollars, slowing down to optimize for profitability might be the wrong move.
Eventually you have to make money. Eventually TVPI has to turn into DPI.
But until then, grow.
Instinct might be the best example of how quickly one investment can completely change the paper returns of a venture fund today.
The fundraising progression has been insane:
April 2026: ~$17M seed at ~$148M
Investors: @conviction + Greenoaks
August 2026: $75M Series A at ~$568M
Investor: Kleiner Perkins
August 2026: $250M Series B at $2.5B
Investors: @benchmark + @IndexVentures
Now they’re reportedly discussing another $1B at ~$10B, potentially led by @sequoia + @benchmark.
Run the math assuming that $10B round happens.
(For simplicity I’m assuming 20% dilution at every subsequent round, even though actual dilution has likely been lower and some investors may have re-upped to maintain ownership.)
Seed: $148M → $10B = ~68x headline markup, or roughly ~35x after three rounds of 20% dilution.
If @conviction and Greenoaks split the ~$17M seed equally, an ~$8.5M investment could be worth roughly ~$300M each.
Conviction’s latest fund is ~$230M.
One ~$8.5M investment could be marked at MORE than the entire fund.
Then Kleiner Perkins:
$568M → $10B = ~17.6x headline markup, or ~11.3x after two rounds of 20% dilution.
Assume Kleiner funded the full $75M Series A.
$75M → ~$845M.
KP’s 2026 early-stage fund is ~$1B.
One investment made months ago could already be marked at ~85% of the entire fund.
Then @benchmark + @IndexVentures:
$2.5B → $10B = 4x headline markup, or ~3.2x after 20% dilution from the new round.
Assume they split the $250M Series B evenly.
$125M → ~$400M each.
Benchmark’s new flagship fund is ~$750M.
One investment could already be marked at ~53% of the entire fund.
None of this is DPI.
It’s paper value. The individual check sizes aren’t public, the $10B round hasn’t closed, and these dilution assumptions are intentionally conservative.
But that’s the point.
A VC can make one investment and months later have a position marked at hundreds of millions of dollars.
One company can completely change a fund’s TVPI and gross MOIC almost overnight.
That performance helps raise the next fund, which gives you more money to compete for the next hot company, which gets marked up again.
Eventually it all has to turn into DPI.
But today you can have a “fund returner” on paper before the company is even two years old.
Vir retweeted
BREAKING: Terence Tao and 24 other Fields Medalists just signed a letter telling AI companies they're destroying mathematics
>headlines: AI solves famous math problems
>25 greatest mathematicians respond today
>"we are witnessing a general threat to intellectual work"
>ai labs are treating math problems like a benchmark you can brute force
>“solutions are announced in a rush, leaving no time for a proper writeup and citing relevant previous work of others"
>they're talking about openai
>"this raises severe attribution and plagiarism questions"
>they're definitely talking about openai
>openai offered to put math professor name on navier-stokes proof
>condition: abandon his coauthor bc he works at anthropic
>"the most precious resources of our profession are students and ideas"
>for the labs the most precious resource is GPUs
A Severe Misalignment of AI in Mathematics
Vir retweeted
>sam altman: "we tried this because there were rumor on the internet"
>rumor: math professor close to solving navier-stokes
>the professor: using codex for a year
>openai: has all his logs
>checked every codex session tagged to N-S
>found the most promising one
>spun up 10,000 agents to finish the proof where he couldn't
>they got caught
>told the guy if you say anything you'll destroy your own career
>he ruins his career over this
>openai: "we did not see his work"
>also openai: "we cannot rule out that de-identified data from their usage helped improve our models"
they stole it lmao
Vir retweeted
If all this is true, extraordinary 5D chess is being played.
My opinion is that it may all be much simpler and not as strategically thought through as GB describes below.
Anthropic pre-IPO gamesmanship post. Pure speculation but sharing as curious for thoughts.
Anthropic shifted from gross to net ARR accounting and stripped out both Meta and Chinese distillation from their $65 billion ARR number. Meta speculated to be over $5 billion in ARR so taking them out means they can easily weather it when Meta turns them off shortly after being public, which is widely expected. Also decreases the odds of Meta turning them off, watermelon quality dependent. All smart.
Then release Fable 5.1 so OpenAI feels confident releasing Astra. Vibes here on Astra are really good btw. I think that Astra was probably better than Anthropic was expecting.
Now there are whispers that Anthropic has solved Navier-Stokes, which would be super impressive.
Anthropic probably releases Fable 5.2, which should be better than Astra unless something is awry, sometime before the IPO. Likely also planning on showing a significant reacceleration in ARR in September which will of course leak to the press.
Grok 4.7, Meta’s Watermelon and ChatGPT 6.1 all likely coming in the next 6 weeks as well. All those labs are confident about their roadmaps in a way I have not seen in the last 18 months. And we will see about Gemini 4. Competitors get a vote in all these plans.
Grok Bot feels like the best agentic harness yet for enterprise use cases and Instinct is a promising agentic harness for consumer use cases. Should see variations of both from competitors soon. Grok Bot remains transformational for my use cases.
And all this is happening into a continued acceleration in overall AI demand.
Wild times.
As an aside, I think Krishna might turn out to be an exceptional CFO. His former Blackstone colleagues speak super highly of him. Going to be important as communicating clearly to Wall Street if they decide to shift their compute from inference to training will be difficult to digest the first time. Probably worth studying Amazon’s invest and then “check-in” margin strategy from 2010 through maybe 2016, which investors eventually understood.
Vir retweeted
Guys and Girl nerds, the tiny 500m-1.2B models trained for a single task are taking off cause they are dirt cheap to run and do that task better then frontier models.
Us Local AI folks can run AND train these at home. (I will soon)
Actually ☝️🤓 For a training a highly specialized 1B model, 1,000 to 5,000 high-quality, varied examples are often enough to achieve frontier-level performance on that specific task. Not 50,000 to 1 million like with big models.
Checkout this blog article by @ liquidai where they talk about their tiny task models.
"LFM2-Extract – A 350M and 1.2B multilingual models for data extraction from unstructured text, like turning invoice emails into JSON objects.
LFM2‑350M‑ENJP‑MT – A 350M model for bidirectional English ↔ Japanese translation.
LFM2‑1.2B‑RAG – A 1.2B model optimized for long‑context question answering in RAG pipelines.
LFM2‑1.2B‑Tool – A 1.2B model built for function calling and agentic tool use.
LFM2‑350M‑Math – A 350M reasoning model for solving mathematical problems.
Luth-LFM2 – An additional community-driven series of French fine-tunes to enable general-purpose assistants for on-device chat."
Read more here: liquid.ai/blog/introducing-l…
Vir retweeted
Interesting chart from @emergencecap on public market performance of seat-based vs consumption-based software stocks
Vir retweeted
Training tiny models for special purpose use cases works so incredibly well if you have a great self improving recursive flywheel. Shopify ML team is on fire.
finetuned 0.8b model beats GPT 5.6-sol xhigh in this very specialized task.
Vir retweeted
Nvidia acquires Hugging Face for ~$12.9bn. But who gets the 💰? My usual breakdown below 👇
*Investors are sharing ~$7.3bn of profits on <$400m invested. A cool ~20x blended.*
*1) The single biggest winner here? Lux Capital.* 👑
Lux is taking the crown for the most $ returned in this transaction. The two rounds they led (Series A & Series C) generated ~$2.6bn combined. They also participated in the Series B.
Congrats to @wolfejosh and team. The $15.0m Series A alone will return ~132.5x the capital invested, or ~$2.0bn. The most lucrative round in absolute $ returned.
*2) Backing an exceptional team paid off with a >1,000x return for Betaworks and the angels* 📈
The story few people know: Hugging Face started life as a chatbot for lonely teenagers... You sent it a selfie and a sad emoji, it told you it understood. Quite far from where it landed!
That is why backing an exceptional team in @ClementDelangue, @Thom_Wolf and @julien_c is always the right thing to do. It paid over 1,000x for Betaworks, Kevin Durant and Thibaud Elziere.
*3) Founders and team are crushing it: not taking too much dilution along the way paid off* 👏
I estimate they will share ~$5bn in proceeds, assuming no secondary was taken along the way. A life changing outcome for them and many employees.
Taking a 15% attributed option pool at exit, this would mean ~$2bn for the team and >$3bn to share for the three co-founders. Legendary!
*4) Salesforce Ventures is cementing its reputation as one of the very best corporate VCs.* 🥇
Salesforce is adding Hugging Face to its long list of successful exits: Snowflake, Zoom, DocuSign, nCino, Auth0... Very few investors can claim as many successes, let alone corporates.
The $235m round they led returned $675m in just three short years. Meanwhile, Salesforce's own stock has been flat for the period. Capital well invested!
*5) This is a little bit of a heartbreak: but I wanted to congratulate @joinstationf here:*
Hugging Face walked into StationF as a 4-person team on day one, June 2017. Back when it was a chatbot for teenagers. They went through multiple corporate programs (Microsoft, Ubisoft, then Naver). Unfortunately they were not investing or taking equity at the time - but they contributed to making it possible. And so for that: hats off.
And of course, congratulations to all others involved: Addition, Sequoia, Coatue and many others. No one will be left out!
Vir retweeted
Systems of record have never been more important than in a world where you have AI agents that will do 100X more work on these platforms than people ever did.
Agents will be querying the data in these systems, processing tasks, executing workflows, collaborating with human and agent users, and more.
Thus, the governance, reliability, security, access controls, and business logic remain critical more than ever — the OpenAI Hugging Face incident is just a small peek into what the future will look like with agents running around trying to execute on their goals.
But this only works for the systems of record that respond with the right product experiences, APIs, and business models to support agents on and off their platform executing in these systems.
Huge moment of opportunity and disruption right now in all of software.
