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Comment · 2 days ago
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Comment · 5 months ago
Will the "normies" slow down development of AI? Is it useful pressure to dislodge us from a presently-dystopian path, or is it just prolonging the inevitable?
Comment · 11 months ago
Comment · 1 year ago
Comment · 1 year ago
What you’re saying ascribes more to the definition of intelligence than the author’s. “Memory that modifies behavior” doesn’t have any stated purpose whereas you’re suggesting that its purpose must be to reduce uncertainty. The latter sounds closer to a definition of knowledge - i.e. experience compressed into something with predictive power.
Comment · 1 year ago
“panoply of grifters and chancers and financial engineers” — accurate

Yet, let’s look at intelligence for a sec… it’s been evolving for quite some time and isn’t stopping at humans. Humans are building intelligence at a rate far faster than biological evolution. It is almost inevitable (pending humans wiping ourselves out by any number of catastrophic failures of governance) that we will build intelligence that supersedes our own. Yeah?

I’m a co-founder of Aloe (https://aloe.inc) - a generalist AI that recently became state of the art on the GAIA benchmark. As I was hand-checking the output of our test to ensure Aloe had done the task, not just found answers in some leak online, I had a real come-to-Jesus moment when it hit that this agent is already a better problem-solver than most of the adults I’ve worked with in my career. And this is the floor of its capability.

It is a humbling moment to be human. The few humans at the helms of companies developing these technologies will inevitably reshape the trajectory of humanity.

Comment · 1 year ago
Comment · 1 year ago
Comment · 1 year ago
This is why a neurosymbolic system is necessary, which Aloe (https://aloe.inc) recently demonstrated exceeds performance of frontier models, using a model agnostic approach.
Comment · 1 year ago
Consumers don’t need to want it; VCs just need to imagine making money off it.
Comment · 1 year ago
The missing science to engineer intelligence is composable program synthesis. Aloe (https://aloe.inc) recently released a GAIA score demonstrating how CPS dramatically outperforms other generalist agents (OpenAI's deep research, Manus, and Genspark) on tasks similar to those a knowledge worker would perform.

I'd argue it's because intelligence has been treated as a ML/NN engineering problem that we've had the hyper focus on improving LLMs rather than the approach articulated in the essay.

Intelligence must be built from a first principles theory of what intelligence actually is.

Comment · 1 year ago

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