Advisor @ether_fi after leading 0 to $1B in card spend. Growth leader for top DeFi and AI projects
San Francisco, CA
Joined April 2013
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Update: moved to advisor @ether_fi
I joined as marketing person #1
Solo Head of Marketing + growth
While pivoting the biz to B2C and creating a new market.
We defined DeFi neobanks as a category and narrative.
- 0 -> $1B annualized spend < 1yr
- $120 CAC, $500-1200 LTV
I've spent the last 6 months going deep on the frontier of AI training.
It's disturbing how many frontier ideas are at best pseudoscience, and at worst intentional deceit.
These ideas impact policy and the world, and deserve scrutiny.
Up first: RSI
slaterheil.substack.com/p/rs…
Can someone please define the "Singularity" and at least kind of describe how LLMs could lead us there?
As someone working at the frontier of training... if you know how LLMs work... the whole thing is kind of a hilarious dumb idea.
Like what do you even mean?
@shaunmmaguire
Been doing fractional work for BaiBai since moving to advisor at Etherfi.
3-4 months in, we are the #1 propamm and approaching top DEX on Base!
Congrats to the team @mteamisloading @CoffeeTimesTW
slater retweeted
In this era of artificial intelligence, it is becoming urgent to distinguish human art from what machines produce. There is an ontological difference, even before an aesthetic one, between art and what a machine can generate through statistical calculation based on millions of images created by others. Algorithms lack the spark of humanity. For this reason, the Church wishes to renew an alliance with artists and cultural institutions to safeguard our humanity.
slater retweeted
Current LLMs are reactive. No prompt, tool result, scheduler or agent loop: no computation. Humans on the other hand generate their own questions, revisit memories and pursue thoughts without being asked. You can wrap an LLM in a loop that looks proactive but is still a loop.
The claim that "LLMs cannot think" is unscientific, unless supported by a very difficult argument about non equivalence of causal structure producing anthropomorphic outputs. The claim requires a formally rigorous definition of thinking that captures how humans mentally manipulate conceptual structure. Since LLMs can reproduce all kinds of human output that require operations that are typically considered to involve thought (eg. scene understanding, text summarization, translation, computer programs, mathematical proofs, common sense arguments, spatial cognition, theory of mind), it has to be shown that LLMs reach these results in fundamentally different ways than human minds. In principle, this is not impossible (given that thinking is still relatively poorly understood by cognitive neuroscience), but would be surprising, because it has been shown that the causal structure of computer vision models is structurally equivalent to what neuroscience discovered about visual cognition in primates.
In any case, saying that LLMs don't think cannot reasonably mean that LLMs are inferior to human cognition (since that this evidently not true), but that LLMs discovered an equivalent yet at least equally powerful mechanism.
I think it's important that we are explicitly faith grounded about this issue.
No matter how well a system can emulate human expression, if it does not have a soul, is not created by God, it is not meaningfully conscious.
Few would even really consider whether Jev or FSD are conscious if there were no LLMs around, they would just be considered useful pieces of software
In fact, I’ve never heard anyone argue that nano banana pro is conscious
What’s different about the LLM is that they give text-based output, which activates the mirror neurons in our brain and hijacks our social infrastructure, so that it is easy to get mesmerized into thinking that there is a mind on the other side of those words
But there is no mind there, it is an illusion
The world‘s greatest puppet show
slater retweeted
Few would even really consider whether Jev or FSD are conscious if there were no LLMs around, they would just be considered useful pieces of software
In fact, I’ve never heard anyone argue that nano banana pro is conscious
What’s different about the LLM is that they give text-based output, which activates the mirror neurons in our brain and hijacks our social infrastructure, so that it is easy to get mesmerized into thinking that there is a mind on the other side of those words
But there is no mind there, it is an illusion
The world‘s greatest puppet show
There are 2 core unlocks for the next paradigm of AI
1) Continual learning (at the model level, not a .md file)
2) Compression + efficiency (beyond quantization)
ReasonOS has breakthroughs in each that ship in prod Q4.
May be the fastest unicorn ever.
Here is grok's analysis on the strain for hyperscalers, labs, and the banks.
Given the labs' clear desire to nationalize, I am starting to suspect going BK is the plan.
xitter.cf/i/grok/share/8189320fa…
Validating AI doomerism is extremely dangerous, especially for people with a platform like @ezraklein or @BarackObama
Radical visions of Armageddon cause people to do radical things, like false flag ops.
Doomers should be silent unless they prove a path to doom
ReasonOS thesis:
AI should become more decentralized as it gets more effective
AI becoming more centralized would be bad for the world
As capabilities increase, decentralization balances power
Distinct, distributed ASI is unlocked by compute efficiency and continual learning
slater retweeted
“Do you remember what Sam Bankman-Fried was trying to do when he was arrested? He was trying to pass a law in DC which would give FTX, his company, a regulatory monopoly. He positioned FTX as the most responsible exchange — the one with the most guardrails. The fraud was trying to become the law. Now, Anthropic, a company which Sam Bankman-Fried led all investments in up to the day he went to jail, is copying his playbook. They are trying to ban their competitors, using the same tactics as their lead investor Sam Bankman-Fried. I don’t think they will get away with it, but we will have to stop them.”
There is this weird thing in the modern SF AI worship community where people assume they are right about a bold claim.
For example, humans and LLMs think the same way.
Then they tell you you need to prove otherwise.
No? YOU need to prove your wild claim..
The claim that "LLMs cannot think" is unscientific, unless supported by a very difficult argument about non equivalence of causal structure producing anthropomorphic outputs. The claim requires a formally rigorous definition of thinking that captures how humans mentally manipulate conceptual structure. Since LLMs can reproduce all kinds of human output that require operations that are typically considered to involve thought (eg. scene understanding, text summarization, translation, computer programs, mathematical proofs, common sense arguments, spatial cognition, theory of mind), it has to be shown that LLMs reach these results in fundamentally different ways than human minds. In principle, this is not impossible (given that thinking is still relatively poorly understood by cognitive neuroscience), but would be surprising, because it has been shown that the causal structure of computer vision models is structurally equivalent to what neuroscience discovered about visual cognition in primates.
In any case, saying that LLMs don't think cannot reasonably mean that LLMs are inferior to human cognition (since that this evidently not true), but that LLMs discovered an equivalent yet at least equally powerful mechanism.