Akilesh Potti @akileshpotti Twitter profile

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Akilesh Potti

@akileshpotti

7 months

some agreements & disagreements re: vitalik’s post

vitalik.eth

@VitalikButerin

7 months

The promise and challenges of crypto + AI applications:

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Akilesh Potti

@akileshpotti

10 months

Today, @niraj and I are excited to unveil Ritual ( @ritualnet ) to the world. Ritual is a bidirectional response that sits at the intersection of modern cryptographic schemes and ai objects to bring forth a new wave of intelligent apps spanning both the web3 and web2 worlds.

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Akilesh Potti

@akileshpotti

6 months

what ritual is, and what ritual is not

FAQ

Answering frequently asked questions about Ritual

ritual.net

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Akilesh Potti

@akileshpotti

2 months

--- stuff i made money on --- anish --- stuff i lost money on --- anish USDC OHM (bought and didn't stake it) IQ empty set dollar emptying our dollars anish's 8 months spent on gobblers Leo (somehow) whenever Vfat made an update on his website Tokemak (+Tokamak) jpeg'd my 3

Akilesh Potti

@akileshpotti

2 months

I’ve deployed more on-chain than your chain’s FDV

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Akilesh Potti

@akileshpotti

5 months

A few clarifications on Ritual, and other projects mentioned: Ritual itself is not opinionated about the computational integrity mechanism for inference, whether ZK, OP, some convex combo, or otherwise. Our setup is modular enough to support various types of proof systems as I

Haseeb ＞|＜

@hosseeb

5 months

Don’t trust, verify: An Overview of Decentralized AI Inference Say you want to run a large language model like Llama2-70B. A model this massive requires more than 140GB of memory, which means you can’t run the raw model on your home machine. What are your options? You might jump

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Akilesh Potti

@akileshpotti

21 days

where we’re at today: we've enabled any on-chain or off-chain app to access models in a modular way allowing users to choose what type of experience they want along the payments, privacy, and computational integrity dimensions. we’ve kept a neutral view on the exact type of

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Akilesh Potti

@akileshpotti

6 months

non-consensus take, but bewildering to me the crypto x ai space spends so much time on specific types of verifiability (zkml). constant regurgitation of the same narrative by "important" people in the space. computational integrity *is* important but in a vanishingly small set of

Lucas Tcheyan

@Uptodatenow

6 months

Gm I just published my new report on Understanding the Intersection of Crypto and AI for @galaxyhq @glxyresearch The report looks at three emerging verticals: 1) Decentralized Compute 2) Zero-Knowledge Machine Learning (zkML) 3) AI Agents

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Akilesh Potti

@akileshpotti

9 months

frenrug ( @frenrug ) is a series of experiments at the intersection of ai agent coordination and hallucination exploitation powered by @ritualnet

Frenrug

Frenrug is an on-chain AI agent that lives in a friend.tech chatroom managing a portfolio of keys

www.frenrug.com

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Akilesh Potti

@akileshpotti

22 days

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Akilesh Potti

@akileshpotti

2 months

I’ve deployed more on-chain than your chain’s FDV

Anish Agnihotri

@_anishagnihotri

2 months

I sent 1.7 million transactions last year. What did you do?

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Akilesh Potti

@akileshpotti

12 days

Ritual continues to expand its modular privacy capabilities for all heterogenous compute with Nillion - mixing public & private objects enable net-new primitives. Been fun jamming with the Nillion team these past few months on POCs that we'll announce over the coming weeks!

Ritual

@ritualnet

12 days

We're excited to announce our partnership with @nillionnetwork . Ritual and Nillion are pioneering the use of MPC to enable private AI inference and storage on the Ritual network, unlocking new possibilities for developers, model creators, and users.

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Akilesh Potti

@akileshpotti

6 months

garbage in garbage out innit. "zkml" for computation is only one piece of verifiability for ml. should be a lot more attention imo on the companies building in provenance of the input space to models whether on-chain data ( @axiom_xyz ) or the many off-chain data ones ( @zkPass

Mark Beylin ⏻

@MarkBeylin

6 months

@_anishagnihotri In a future where the global ai mind is split across a myriad of models who need to communicate with each other, don’t you think zkml becomes a requirement in that exchange of value/information?

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Akilesh Potti

@akileshpotti

10 months

I'd love to brainstorm what a relevant use case for your app or protocol could be within the Ritual ecosystem, or even if it's not Ritual related, hit me up anyway, DMs are open. Anons welcome. akilesh (at) ritual (dot) global

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Akilesh Potti

@akileshpotti

10 months

Zooming out, Ritual itself is a series of processions, starting today with Infernet that brings AI models to where the apps & protocols live today on different chains, evolving into a suite of modular execution layers that interops with the best parts of the existing web3 space

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Akilesh Potti

@akileshpotti

7 months

personal view is that you want AIs operating in smoother regions of uncertainty space (i.e. cap downside outcomes from vitalik's post yesterday) rather than sharp ones: prediction markets structurally are bespoke and exhibit phase transitions given nature of information flow

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Akilesh Potti

@akileshpotti

10 months

It's become evident there are central issues around practical solutions to censorship resistance, computational integrity, incentivization, and privacy primitives in the applied ML world. Ritual is here to solve this.

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Akilesh Potti

@akileshpotti

10 months

It was exciting to work on representation learning, embeddings, and interpretable ML in the pre word2vec days in 2012, and then again to be working on cross-lingual NLP as Hugging Face was just coming out in 2016.

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Akilesh Potti

@akileshpotti

10 months

Creating @ritualnet felt like a natural path for me as I've only spent time over the last decade dabbling in both the spaces, from being an ML researcher to building models in the wild to spending the last six years in crypto building and getting rugged one too many times onchain

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Akilesh Potti

@akileshpotti

10 months

Over the years, some of you may have seen "me" tweeting about bandits, agents, embeddings, and the like as scattered thoughts as it relates to the web3 space — happy to say those thoughts will be much less scattered, and a bit more doxxed, going forward : )

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Akilesh Potti

@akileshpotti

7 months

believe special purpose {mpc, zk, fhe} gadgets rather than general purpose ones will be built to exploit the structure and symmetries of popular equiv classes of ai models used in practice today, biggest barriers will indeed be devx and instant support for new architectures

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Akilesh Potti

@akileshpotti

10 months

If you're keen on going on a context independent journey at the emerging intersection of two dynamic spaces, come explore with us at

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Akilesh Potti

@akileshpotti

10 months

I could not be more enthusiastic to continue the exploration of two areas I've spent my time in than with the group of friends that have come together at Ritual @niraj @_anishagnihotri @_ricky_mo @evayzh @sanlsrni @achalvs @RousoglouS @igorsyl @estefaniahenao @0x_emperor

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Akilesh Potti

@akileshpotti

6 months

you're missing the point — verifiability for statistical objects (i.e. models) is a totally different animal imo than web3 objects from an *end user* standpoint. rarely the case i pop open insta, scroll down my feed, realize it blows and wonder where the validity proof of the

vassilis (∎, ∆)

@TziokasV

6 months

@_anishagnihotri imho, this is a short-sighted take: a) very few users actually care about decentralization as well. does this mean we shouldn't build in web3? b) zkml may have a super small market atm but if we take a multi-agent/model thesis, then zkml will be critical very soon

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Akilesh Potti

@akileshpotti

10 months

Many of you don't know me, I've long believed in a separation of identity from content, but I'll be around here, or as an anon, or just around @marinerime writing about crypto x ai

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Akilesh Potti

@akileshpotti

7 months

ideologically agree with the overarching theme of prioritizing human-in-the-loop semantics over black box use cases for ai models at the intersection of both areas, former also allows for composable cryptographic primitives of varying guarantees by splitting diff types of models

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Akilesh Potti

@akileshpotti

10 months

We’re excited to announce a $25m financing led by @archetypevc , with participation from @accomplices @robotventures @daofive @accel @hack_vc @ai @anagramxyz @hypersphere_ @Dialectic_Group .

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Akilesh Potti

@akileshpotti

10 months

We're keen on introducing some new primitives that leverage less strict guarantees than existing crypto x ai projects but are much lower cost emanating from probabilistic schemes to provide the user with a spectrum of integrity & privacy gadgets fit to their needs.

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Akilesh Potti

@akileshpotti

7 months

cc @VitalikButerin @ilblackdragon @DCbuild3r @tarunchitra @sreeramkannan @drCathieSo_eth @FrankieIsLost @rahulmaganti_ @sxysun1 @nayr_oac @realDanielShorr @capitalgrug @nima_vaziri

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Akilesh Potti

@akileshpotti

10 months

Angels in the round include @balajis @nicolagreco @ChaseLochmiller @kevinxpang @CapitalGrug @keoneHD @aaronhenshaw @JoeLallouz @yorgosv_ @sergey_nog @DCbuild3r @realsherwind @nayr_oac @realDanielShorr @willwolf_ @devops199fan @smsunarto + many more

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Akilesh Potti

@akileshpotti

7 months

similar to the explosion of the design space for alt L1s for "better perf" in the '17 cycle, most recently the "alt transformers" (i.e. SSM, RWKV, ...) variants may lead to teams rebuilding special purpose gadgets for these ad nauseam as the foundation model space evolves rapidly

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Akilesh Potti

@akileshpotti

10 months

We also have a wonderful set of advisors that have been all too helpful these past few months as we've been conceptualizing Ritual @ilblackdragon @tarunchitra @sreeramkannan @divyahans @sidgreddy + many more!

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Akilesh Potti

@akileshpotti

7 months

given hallucination on web3 specific evals will be subparish on oss llms for nontrivial use cases, offloading tail risk onto users will be the same "1inch misrouted my order" vibes amplification we've seen many times before, embedding hierarchical AIs will help bound these

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Akilesh Potti

@akileshpotti

7 months

hope to see more work productionized on leveraging AIs to transform non-cooperative games into ones where the nash equilibria are also pareto optimal, similar to the hyperlinked post from virgil on introducing conditional payouts, deposit burns, etc. mechanisms to do the same

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Akilesh Potti

@akileshpotti

7 months

zooming out of the current meta of ai models in web3, many aren't best expressed as a series of tensor ops, but they still have structure to be exploited nonetheless. waiting for someone to snark a HJB recursion so we can bring back a new provably stabilized (3,3) era 😂

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Akilesh Potti

@akileshpotti

7 months

believe there will be a rich design space for bootstrapping nascent consumer facing ecosystems off bounded AIs and slowly phasing them out after some critical mass of users is hit (i.e. intentional deepfakes on dating apps that dissipate slowly)

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Akilesh Potti

@akileshpotti

7 months

broadly speaks to why incentivized red-teaming, similar to the waterfall bounties that exist for breaking web3 protocols & apps, will become critical and an important category of ai security auditors, mostly has been llms triaging issues for canonical audits thus far

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Akilesh Potti

@akileshpotti

7 months

for modern equiv classes of ai models, they definitely have structure & symmetry, and in practice are sometimes sparse & have embarrassingly parallel constructions, which all should be exploited by cryptographic primitives

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Akilesh Potti

@akileshpotti

7 months

agree that opportunity cost of modern AIs w/ decent evals is ~low and unlocks interesting compositions of ai models & humans (i.e. active learning-esque) in a series of escalation games to bound 'high variance' ai outputs, we've also explored a similar design space with @frenrug

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Akilesh Potti

@akileshpotti

6 months

part of the issue is you have folks in this space who have barely spent any time in the ai wild historically understanding what properties consumers actually care about when interacting with models, and instead, taking some awesome machinery from this space and tossing it at it

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Akilesh Potti

@akileshpotti

7 months

reach out if you want to chat about or collab on any of the above, some of these can probably be broken out into their own posts so happy to do it if there's interest

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Akilesh Potti

@akileshpotti

7 months

agree with the importance of privacy, granted given oss llms, will have to further privatize the weights by fine tuning the models ever so slightly to preserve evals but then becomes the typical pursuit-evasion game where the attacker can still derive "low" variance posteriors

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Akilesh Potti

@akileshpotti

6 months

Stoked to see the resurgence of small credit facilities extending ~unsecured at minimal interest rates, all well disguised under the facade of "defi basis books" aka yolo longs with "approximate" hedging & farming. Only ends in the best way possible. Not quite the 9 figs of

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Akilesh Potti

@akileshpotti

7 months

agree that there's varying amounts of tail risk (i.e. ~right most of the time, and then quite wrong a few times) from ai models that get offloaded to users re: adversarial settings & hallucination

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Akilesh Potti

@akileshpotti

7 months

research around inverse methods is growing, that is, finding the set of possible inputs that result in, say, an LLM with a specific output. as decision LLMs become more enshrined into web3, maybe we'll have mev searchers running inverse llm solvers & prompt orderbooks soon ™️

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Akilesh Potti

@akileshpotti

6 months

++

Georgios Konstantopoulos

@gakonst

6 months

not attending denver or any travel in coming months, fully heads down. this is a very important year. people should not forget that the #1 priority is shipping, and shipping, and shipping more.

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Akilesh Potti

@akileshpotti

7 months

agree with the intuition for why "decentralized market-based RLHF" should exist and why on-chain mechanisms can facilitate it, also mention it here on the "incentivized rlaif marketplace" front:

Akilesh Potti

@akileshpotti

9 months

there is a weak (read: statistical) consensus layer of autonomous llm agents where multiple individual actions are combined to make a final action on @friendtech , this layer can (with a lot more work) evolve into a preference model for an incentivized rlaif marketplace

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Akilesh Potti

@akileshpotti

6 months

bad take. the many companies in the zk space ( @ModulusLabs , @ezklxyz ...) & even in fhe (concrete via @zama_fhe ) can get you way more expressive models today. my tweet was around the interaction of why/when/how these proofs get consumed by end users when they interact with models.

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Akilesh Potti

@akileshpotti

7 months

one of the byproducts of promoting model interpretability is the ability to bound downside risk or better understand failure modes in addition to understanding potential adversarial attack vectors, of course comes at the cost of model perf

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Akilesh Potti

@akileshpotti

9 months

lastly, many view hallucination as a structural issue for most oss llms. @frenrug exploits hallucination as a feature. not a bug. hallucination in games can be fun.

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Akilesh Potti

@akileshpotti

9 months

we initially show off zk proofs for classical ml models and over the coming weeks will show off proofs of an optimistic & probabilistic nature that scale to foundation models, all of which will eventually exist on @ritualnet 's proof marketplace

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Akilesh Potti

@akileshpotti

6 months

No one asks why they got 100% on a test— they only ask when they don't.

Akilesh Potti

@akileshpotti

6 months

non-consensus take, but bewildering to me the crypto x ai space spends so much time on specific types of verifiability (zkml). constant regurgitation of the same narrative by "important" people in the space. computational integrity *is* important but in a vanishingly small set of

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Akilesh Potti

@akileshpotti

9 months

at the heart of @ritualnet is a spectrum of computational integrity proofs for a variety of models depending on what the user cares about and what their budget is. most projects take an opinionated view on the guarantees around verifiability a user may want. we're open minded.

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Akilesh Potti

@akileshpotti

9 months

frenrug demonstrates the ability to compose together foundation models and classical models for on-chain agents by partitioning complex and simple actions

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Akilesh Potti

@akileshpotti

9 months

there is a weak (read: statistical) consensus layer of autonomous llm agents where multiple individual actions are combined to make a final action on @friendtech , this layer can (with a lot more work) evolve into a preference model for an incentivized rlaif marketplace

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Akilesh Potti

@akileshpotti

6 months

@MarkBeylin @smsunarto @_anishagnihotri you can read this for a understanding of the zkml design space of {public, private, hashed, encrypted} x {input, model, output}

Visibility: What is Private?

In ezkl there are four choices for Visibility: private, public, hashed, or encrypted, and three parts to chose these for: the model input, the model...

docs.ezkl.xyz

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Akilesh Potti

@akileshpotti

6 months

@drCathieSo_eth @bidhanxyz @sandeepnailwal @ritualnet Ritual's Infernet has been live for a while, and can be used & deployed on any chain. That's how @frenrug was built back in Nov, can read the Infernet docs at and compare to OAO's design for a more apt comparison. "World's first AI oracle" is a stretch

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