Neel Master

Co-founder/CEO @cedanacorp. Previously: Engooden , @MIT_CSAIL, TL Ventures

[Neel Master @neelmaster]

@gokulr @mustafasuleyman MSFT not using distillation even though they legally could, is a strong signal. They realize they need to pull ahead of the frontier. Unlike OpenAI and Anthropic, they can subsidize tokens to increase the margins of their existing enterprise sw base.

[Neel Master @neelmaster]

@ttunguz Sierra is a clear cut case, but I suspect Devin's abstraction is closer to cost-plus because it's inherently linked to the cost of their token. They succeed there if they can exploit the delta between tokens and the value of the task, but that can vary.

[Howard Luks MD @hjluks]

Don’t let your life 'narrow'.

I’ve been an orthopedic surgeon for 30 years. The thing I watch happen to people — more than any injury or surgery — is what I call the narrowing.

Most of my patients have no idea it’s happening. They think it’s just aging. It’s not...

[Neel Master @neelmaster]

@deedydas Together should be on the list.

[Neel Master @neelmaster]

@demian_ai Insightful post. Agree this is where things are headed. However I question whether Anthropic is "deeply negative". I suspect they throttle tokens for flat fee plans, which stems the bleeding margin. We'll find out about their margins when their filling goes public.

[Neel Master @neelmaster]

@gokulr @mignano @fredwilson If you believe this, then there's a strong argument AI will very soon be able to consistently generate better a thesis than humans.

[Neel Master @neelmaster]

Insightful perspective. Static prefill/decode assignment is the starting point. The challenge with all schedulers is that placement is fixed at deployment. Once inference becomes a disaggregated serving line, the optimal assignment changes with traffic, failures, cache locality, hardware health, SLOs, and cost. @cedanacorp lets operators reshape that line without paying the full cold-start and lost-state penalty every time, by migrating workloads across instances without interruption.

[Neel Master @neelmaster]

@badlogicgames Users and developers treat inference as semantically stateless, but longer context windows make inference inherently stateful. This results in a new set of operational challenges.

[Packy McCormick @packyM]

The future is electromagnetic.

One challenge is that there are ~ten people in the world who can deeply intuit electromagnetism. RF engineering is "black magic."

Arena Physica thinks machines can intuit EM better.

CEO Pratap Ranade & I on AI for EM:

https://t.co/U3CUnqcYPp

[Neel Master @neelmaster]

@bryan_johnson Applaud you for stating a fact that may get you in trouble with many podcasters. It's particularly nefarious because it calls into question the influencers credibiltiy.

[Neel Master @neelmaster]

@endowment_eddie Compliance is innovation.

[Federal Reserve @federalreserve]

Video message from Federal Reserve Chair Jerome H. Powell: https://t.co/5dfrkByGyX

[Neel Master @neelmaster]

@stevesi I wonder if people who decide re-writing code from C/C++ to Rust understand how compilers work. Having tried and tested code over many years >> typesafe code you think will be safer. There is inherent performance difference between the two. It's a mid-twit move.

[Yann LeCun @ylecun]

I think the disagreement is largely one of vocabulary.
I object to the use of "general" to designate "human level" because humans are extremely specialized.

You may disagree that the human mind is specialized, but it really is. It's not just a question of theoretical power but also a question of practical efficiency.
Clearly, a properly trained human brain with an infinite supply of pens and paper is Turing complete.
But for the vast majority of computational problems, it's horribly inefficient, which makes it highly suboptimal under bounded resources (like playing a chess game).

Let me give an analogy: in theory, a 2-layer neural net can approximate any function as close as you want. In practice, almost every interesting function requires a impractically large number of units in the hidden layer. So we use multi-layer networks (that's actually the raison d'être for deep learning).

Here is another argument: the optic nerve has 1 million nerve fiber. Let's make the simplifying assumption that the signals are binary. A vision task is therefore a boolean function from 1E6 bits to 1 bit.
Among all the possible such functions, what proportion are implementable by the brain?
The answer is: an infinitesimal proportion.
The number of boolean functions of 1 million bits is 2^(2^1E6), which an unimaginably large number, about 2^(1E301030) or 10^(3x1E301029).
Now, assuming that the human brain has 1E11 neurons, and perhaps 1E14 synapses, each represented on, say, 32 bits. The total number of bits to specify the entire connectome is at most 3.2E15. This means the total number of boolean function representable (computable) by the entire human brain is at most 2^(3.2E15).
This is a teeny-tiny number compared to 2^(1E301030).
Not only are we not general, we are *ridiculously* specialized.
The space of possible function is vast.
We don't realize it because most of those functions are unfathomably complicated to and us and look completely random.
I love this quote from Albert Einstein: "the most incomprehensible thing about the world is that the world is comprehensible"
It's pretty incredible that among all the random ways the world could be organized, we can actually find a way to understand a tiny part of it.
The part we don't understand, we call entropy.
Most of the information content of the universe is entropy: things we simply cannot understand with our feeble minds and choose to ignore.

[Neel Master @neelmaster]

@juliachaigneau Any recs for travelers coming to Ahmedabad?

[Neel Master @neelmaster]

@01101101arMar I admire this level of obsession.

[Neel Master @neelmaster]

@bryan_johnson You can acheive this with meditation. I hope you study extensive mediation like Vipassana and other forms next!

[Neel Master @neelmaster]

@mikulaja The founders all resigned a few years into the company to be replaced with a CEO.

[diplo @diplo]

I was 20 when I first came to India with nothing but a restless mind and an old Enfield I bought from a friend in Delhi who taught me to ride in one dusty afternoon. He took my money, flew back to Florida, and left me with one rule: don’t hit a cow, and only ride between 2–6 a.m. if you want to survive the heat and smog. Somehow, that became a philosophy for everything that followed.

I crossed the country like a kid inside a dream — Calcutta to Delhi to Rishikesh — sleeping on the bike when I had to, chasing chai stalls to stay awake, tossing the bike on trains when I could afford it. I swam in the Ganges, did yoga with elders who moved like water, bought vinyl in back-alley shops, fell in love the way only your twenties let you, and wrote long confusing emails to my mom from glowing village internet cafés.

In Gujarat I stopped long enough to help with earthquake relief, eat thalis in strangers’ homes, and learn “Kem Cho” and “Majama.” India didn’t just teach me independence — it cracked me open creatively. It showed me how improvisation is its own kind of discipline, how getting lost is a form of education.

I never imagined I’d be invited back years later to collaborate with artists I once watched on café computers — working with actors like SRK, making videos like “Lean On” that crossed billions of views, nearly dying during spiritual side quests in Leh and Varanasi, falling for Bollywood sweethearts, and still believing every strange turn meant something.

Twenty-five years later I returned to these roads, riding nine hours a day across the Himalayas on a much newer Enfield. And then — perfectly — I ended up performing at a massive Enfield festival in Goa and celebrating afterward in a motorcycle garage, as if time folded back on itself.

Two decades have changed India and me both. But every time I come back, I feel the same truth: growth happens when you surrender to the unknown, when the road teaches you more than any classroom could.

India was my beginning. And somehow, it still is.

[Neel Master @neelmaster]

Total grift. This goes back to what Roelof Botha was saying is the systemic issue with VC today. Too much capital.

https://t.co/ETFbc56NlN

[Matt Grimm @mttgrmm]

Secondary markets are rife with fraud and bad actors, and it pains me to see these bottom feeders profiting off Anduril's growth while fleecing retail investors through unreasonable or opaque fee structures.

In this week's episode of nonsense, @teamignitevc (a fund we've never taken a meeting with or had any contact with whatsoever) founded by @brianrbell (who we've never met) is soliciting investors via a public Google Doc to invest in an SPV that will in turn invest in another SPV that will in turn potentially enter into a Forward Contract with a (supposedly, though unnamed) early Anduril employee: https://t.co/33d3lRCxTr

Few problems here.

First off, so-called "Forward Contracts" are notoriously hard to settle in private companies, and counterparty risk is extremely real (e.g. what about the many complicating corner cases like acquisitions where shares don't "trade" or marriages/divorces/deaths where ownership of underlying shares is complicated)... just generally a risky structure to close that I don't think most folks actually understand.

Second, this "Deal Memo" includes basically no details about Anduril's performance, no revenue figures whatsoever, no product specifics... almost as if it's soliciting investors to invest on hype and momentum and not fundamentals. Generally I'd advise folks to be skeptical of any "deal memo" lacking basic details.

Third, Forward Contracts are explicitly disallowed by Anduril's stock plan and bylaws, as we detail here: https://t.co/laVUsB1kfR ... which means that Anduril will never consent to Team Ignite's SPV actually taking possession of these shares while we are privately held. Zero chance.

And finally, the memo spends most of it's time talking about the structure and fees... which are INSANE. A double-layered SPV with all legal and administrative costs passed through, in addition to an 8% upfront fee, 3% annual fee for two years, 20% carried interest, and... the craziest part... an implied price per share that is completely insane (in this case, the implied pps is ~115% higher than the most recent preferred raise from like 9 months ago). Flattered, I suppose, but also puts these investors in an almost absurd position by paying more than double the pps of our most recent transaction. 😬

As stated at the top, I don't know Brian or Team Ignite at all, maybe they're kind wholesome people and this is all a big misunderstanding... but if I were an investor looking at this "opportunity," I'd run for the hills.