kodjo

[Rei @rei_labs]

Introducing Adapt-1 Machina: Learning Continuous Control Sequences

With Adapt-1 Machina, we explore how continuous sequences of machine controls can be learned through reinforcement learning, starting with coarse outcome feedback and without demonstrations or a critic.

[reisearch @0xreisearch]

Can the fly turn sensory evidence into a decision? In this short experiment it has to earn bananas and solve the captcha. We follow its retinal-contrast sensory readout as it inspects images.

[Ranulph @RanTheFalcon]

Most projects ship a landing page and a Notion doc.

Then disappear until good market conditions return, with "big new features" they've apparently worked so hard on...

Study the REAL projects instead.

$REI shipped 181 updates across 11 public repos in the last year.

Gud tech.

[Khalil @A_Keyboard]

https://t.co/Fzw8wMLnKA

[bes @bes_______]

we remove a lil friction

[Rei @rei_labs]

Can Adapt‑1 Preview stay in an interactive decision loop while thousands of outcomes keep changing its persistent decision state?

We finished migrating to the infrastructure intended for public access. Here’s what latency looks like as retained experience accumulates.

[Plata @platacrypto]

Already can tell how dumb this market is when you get a major publication and potential break through and folks decide to sell.

Yeah i get it, it is highly technical and won't matter for most but what $REI is doing is more innovative and on the forefront of AI than any other web3 ai lab.

[Cryptic Tits (npc/acc) @cryptic_tits]

@jessepollak @base base:0x6b2504a03ca4d43d0d73776f6ad46dab2f2a4cfd https://t.co/Amein57oT1

[Plata @platacrypto]

Summary of $REI Token Utility Plans:

• Ecosystem token for access, ownership, attribution, and exchange across the Rei / Unit 00 layer
• Planned settlement currency for marketplaces of Core instances, published knowledge, learned structures, and inspectable traces
• Planned revenue-funded buybacks (not live yet)
• Intended for transparent on-chain marketplace settlements and treasury activity
• Supports future company–token alignment (ownership structure, revenue flows, buyback mechanics)

[Cryptic Tits (npc/acc) @cryptic_tits]

n00b critics tried telling you : "it only learns because a human sets up the task structure for it."

REI new release: they removed that structure and let it figure the structure out itself ... and it kept 95% of the performance.

[mic drop]

[ID @Djureth]

Artificial intelligence university is full of students, but only one learns.

GRei

[Nikita G. 🎲 @Gorev111]

tokenized ai lab on base
@cobie
@jessepollak
@brian_armstrong
study the blog
base:0x6b2504a03ca4d43d0d73776f6ad46dab2f2a4cfd

[Rei @rei_labs]

Introducing Emergence.

It removes learner ontology from Adapt-1’s online learning setup. Observation paths, temporal context, causal variables and action-state bindings can now be induced online from interaction and committed as revisioned state.

Blog : https://t.co/t8eOFCzfki

[consom888 @consom888]

Long term horizon… slowly then all at once - fiat will also be accepted to reduce friction and converted to $REI

[Conan @_Conan0x]

@Dan_Jeffries1 Pretty interesting series of blogs in this direction from @rei_labs along with a free preview api where you can recreate their benchmarks or try out what you want https://t.co/2IR0MdMoYW

[snowyprints @Snowyprints]

“Sometimes an AI does not need to learn a better answer. It needs to learn a better representation of the problem.” base:0x6b2504a03ca4d43d0d73776f6ad46dab2f2a4cfd

[Plata @platacrypto]

https://t.co/qfWUTLxZTc

[Plata @platacrypto]

@1CrypticPoet @base The bluechip AI lab ticker is $REI @rei_labs

[reisearch @0xreisearch]

With the latest feature unlocks of Adapt-1 we wanted to further solidify its structure.

Temporal Context Projection (TCP) and Counterfactual Utility Plasticity (CUP) are rules that you can toggle on/off.

Temporal Context Projection allows the substrate to learn which parts of past experience are relevant to the present decision. So, instead of treating every observation the same way, delayed evidence now becomes explicit and revisable context.

Counterfactual Utility Plasticity instead asks which signals become valuable specifically when combined. Recording predictions before outcomes are known makes possible to evaluate each combination by the predictive utility it contributes beyond its components. That way useful structures are reinforced, harmful ones inhibited, and stale ones allowed to decay under distribution shift.

This has nothing to do with episodic memory, instead CUP and TCP change how retained evidence is transformed into decision state and organized into persistent predictive structure.

TCP and CUP combined make rules whose temporal reach and internal composition can both reorganize online as consequences arrive. TCP learns when the past matters, CUP learns what becomes meaningful together.

Docs : https://t.co/XVRqkwwuZq
https://t.co/4H6mPOnVSz

[AJP @ajp_digital]

@cryptic_tits @jessepollak @base @base has a frontier neolab trading on it, fully liquid, at pre-seed valuations before expansion

https://t.co/I5xqMYmrmU