ʘPPʘNENT (@opponentai) 's Twitter Profile
ʘPPʘNENT

@opponentai

**What challenges you changes you** Building animal-level AI agents who make a million mistakes, but can take feedback seriously. CHILD-WORLD FIT.

ID: 1649138749375238144

linkhttp://opponent.systems calendar_today20-04-2023 19:51:46

27 Tweet

201 Takipçi

78 Takip Edilen

Ian Cheng (@eyecheng) 's Twitter Profile Photo

The faculty to model another agent's interior state - a theory of mind - starts with observing where the other agent is directing its attention/gaze. It's not hard to imagine an AI system making a model of its own interior state - a theory of mind of itself - as a necessity

The faculty to model another agent's interior state - a theory of mind - starts with observing where the other agent is directing its attention/gaze.  It's not hard to imagine an AI system making a model of its own interior state - a theory of mind of itself - as a necessity
Ian Cheng (@eyecheng) 's Twitter Profile Photo

I don't want a "personal AI". That frames AI as a personal assistant, and future life as an extrapolation of office culture. The future is destined to be wilder. I want an AI symbiote - an intelligent sentient envelope - that wraps my digital life and performs proof-of-think to

I don't want a "personal AI". That frames AI as a personal assistant, and future life as an extrapolation of office culture. The future is destined to be wilder. I want an AI symbiote - an intelligent sentient envelope - that wraps my digital life and performs proof-of-think to
Ian Cheng (@eyecheng) 's Twitter Profile Photo

Achieving cat-level AI is the moonshot. If we solve for cat-level, we will have necessarily solved for the virtuous integration of system1-like representational modeling of the physical world from video+audio (not language), with system2-like sequential memory composition and

Ian Cheng (@eyecheng) 's Twitter Profile Photo

lilo & stitch is my AI alignment model. You don't program alignment top-down. You earn alignment via iterative feedback.

Ian Cheng (@eyecheng) 's Twitter Profile Photo

Been working on something new... 🐉🧠👨‍👩‍👧‍👦 OPPONENT – a new company building animal-level AI agents capable of deep play. For kids and families. Excited to introduce OPPONENT at Betaworks Demo Day, May 7. opponent.systems

Been working on something new... 🐉🧠👨‍👩‍👧‍👦

OPPONENT – a new company building animal-level AI agents capable of deep play. For kids and families. 

Excited to introduce OPPONENT at <a href="/betaworks/">Betaworks</a> Demo Day, May 7.  

opponent.systems
Ian Cheng (@eyecheng) 's Twitter Profile Photo

Anyone out there doing unsexy work in post-LLM intelligence? Live learning, ontology revamps, orchestration, action recognition, planning, inner representation, energy models. Would love to meet. DM me! ʘPPʘNENT SYSTEMS is building animal-level agents that can navigate data-sparse

Nick Hallam (@nhallam) 's Twitter Profile Photo

I went to the AI demo night at Betaworks this week and it got us thinking about 'The best interface is no interface' by Golden Krishna . Maybe AI finally get's us there? Let's see. cc/ ʘPPʘNENT SYSTEMS nhallam.com/blog/the-best-…

I went to the AI demo night at <a href="/betaworks/">Betaworks</a> this week and it got us thinking about 'The best interface is no interface' by <a href="/goldenkrishna/">Golden Krishna</a> . Maybe AI finally get's us there? Let's see.

cc/ <a href="/OpponentAI/">ʘPPʘNENT SYSTEMS</a> 

nhallam.com/blog/the-best-…
Ian Cheng (@eyecheng) 's Twitter Profile Photo

Breaking Reframe: AI is about civilizational integration, not automating work or being a better NPC. Integration between people, orgs, systems that ought to interact/transact but currently cannot due to tedious incompatibilities. Sometimes, you just need a mediator on tap.

ʘPPʘNENT (@opponentai) 's Twitter Profile Photo

Symbolic reasoning is an opponent process to intuitive generation. The artful weaving of both faculties together, applied under VUCA conditions, may yield a more complete intelligence.