•Krishna

Founder at @The_Utility_Co | @OsirisProtocol1 | @tucdigibazaar | @lochnesssociety | @thegraineledger | @requiemelectric • Biochem/English/ME

[•Krishna @GenRevoeth]

@BasaltHQ @The_Utility_Co What the @BasaltHQ team has accomplished here is incredible. The fastest and most elegant buildout ever in the typically convoluted payments industry.

[𝘉𝘢𝘴𝘢𝘭𝘵𝘏𝘘, 𝘐𝘯𝘤. @BasaltHQ]

Traditional processing eats 2.9% + $30¢ of every single sale. BasaltSurge bypasses the middlemen to deliver instant, decentralized settlements directly to your business. Card, crypto, or cash. Get paid in seconds, not days.

[David Shapiro (L/0) @DaveShapi]

First impression of Claude 4.8: pretty sharp. I gave it my standard intelligence test (can it solve post-labor economics without searching the internet). It did pretty well.

On the first message (depicted below) it nailed that capital is the primary move as wages erode.

[•Krishna @GenRevoeth]

@DaveShapi Eventually people will realize that digitization of all assets with subsequent tokenization is an important and urgent undertaking.

[•Krishna @GenRevoeth]

@DaveShapi Its greatest impact is in industrial automation and only if sufficiently democratized for optimal access and agency.

[•Krishna @GenRevoeth]

Diving deep into the Theory of Intentionality and Reservoir Computing - where minds meet machines 🤖🧠. Exploring how systems *mean* something, not just process it. Big ideas, bigger implications for AI’s next leap.

[•Krishna @GenRevoeth]

@The_Utility_Co Welcome aboard, automation maestro — your #I3AS game is next-level and we’re here for it. Let’s build the future, one smart system at a time.

[•Krishna @GenRevoeth]

Makes the stock price(s) go up. The cavalier prescription of panaceas is what I have the issue with. Probably causes anxiety in new entrants working on something outside the RNA domain. Also, completely ignores the dogma of biology where intervention isn’t always best option at the transcription or translation level.

[Séb Krier @sebkrier]

People misinterpret the Ramanujan and Einstein examples and assume this just means AGI has to be a super genius otherwise it doesn't count. To me this doesn't seem to be the point; they're illustrations of categories more than thresholds. Demis previously described creativity as falling into three buckets:

Interpolation, i.e. averaging many data points and recombining them, e.g. an image model producing a new photo that would have not been in a dataset before. Extrapolation, i.e. going beyond the convex hull of the training data to produce something experts recognise as genuinely new - we have a lot of examples of this with existing systems, like Move 37 and all the recent maths examples. And thirdly, invention: actually coming up with the game of Go in the first place. It's the third type that existing systems, at least as currently scaffolded/used, appear to lack.

There may be a difference between solving existing conjectures or problems, and actually coming up with the theory in the first place. Language models produce all sorts of new outputs, but the outputs differ qualitatively in kind even if they're novel to varying degrees. Does the new output live inside the conceptual space defined by the training data (interpolation), push outside it along existing dimensions (extrapolation), or reframe the space itself by proposing a new conceptual structure (invention)?

Ramanujan illustrates the depth of intuition and innovation that the third 'true creativity/invention' category represents. There may be recombination and extrapolation as part of that process, but at least so far they don't seem to be sufficient. Of course you can argue that most humans don't do this - when was the last time you invented a new abstraction?

My uneducated view is that this third type of creativity doesn't have to lead to crazy new inventions - obviously inventing the theory of relativity is both more impressive and more *valuable* (and thus depends also on a social aspect and utility), but I think individuals do this third type of creativity in many smaller/micro ways too. For example a teenager on TikTok warping a meme format into something the format didn't previously allow/cater for. This kind of type-3 operation should be observable at small scales, frequently, with low stakes too.

I think it's very reasonable to argue that this is *just* interpolation/extrapolation, but I personally don't think this is all there is. If it was then it should be feasible for e.g. Talkie (the model trained up to 1930s data) to be prompted/scaffolded to create a new abstraction entirely. I haven't seen this, except by teaching it basic coding through fine-tuning - but that's not the same thing, since you're showing it the new abstractions (coding) to start with!

I'm not sure if this is because (a) language models lack the cognitive operation entirely, given the architecture; or (b) it has the operation but lacks the appropriate scaffolding, memory, and process. Maybe it's (b), though I lean towards (a): language models are better at paradigm exploitation than paradigm generation. Of course practically speaking, you don't strictly need this third type of creativity for the technology to be transformative and revolutionize fields; but it's a difference that is still worth highlighting and accounting for, since it also implies certain ceilings determined by the shape of the existing conceptual space.

[May Khanna @may_khanna]

🙄

[•Krishna @GenRevoeth]

@tszzl @davideoks Honestly quite sad to find out that you were pretty much hired as the rhetoric machine for the slop generator. Tell me it isn’t true.

[•Krishna @GenRevoeth]

@tszzl @daniel_271828 Look into @The_Utility_Co if you haven’t already.

[•Krishna @GenRevoeth]

@DaveShapi People will control automated industry with varying degrees of control to produce whatever they want and at any level of abstraction they want. True agency.

[Genesis AI @gs_ai_]

We are back. After one year of quiet building.

Introducing GENE-26.5, our first robotic brain that takes a major step toward human-level capability.

For years, robotics has struggled to learn from the world’s largest and valuable data source: Humans.

Solving it means rethinking the whole stack from the ground up:

- A robotics-native foundation model.
- A 1:1 human-like robotic hand.
- A noninvasive data collection glove for motion, force, and touch.
- A simulator that turns weeks of experiments into minutes.

GENE-26.5 is trained across language, vision, proprioception, tactile, and action. We designed a set of tasks to test how far we can go with this new paradigm.

Fully autonomous, 1x speed, one model, same weights. (Enjoy with sound on)

We are approaching the endgame for robotics.

And this is just a beginning.

[•Krishna @GenRevoeth]

@DaveShapi I think we need a combination of UBA (universal basic assets), UBI, and UBC for a truly equitable world. UBA is in consideration of advances in materials technologies and advanced fabrication such as additive manufacturing for home construction.

[•Krishna @GenRevoeth]

@cdixon Check out @The_Utility_Co and @BasaltHQ

[•UtilityCo @The_Utility_Co]

Homesteading was the government’s response to the American Frontier. What is the equivalent response to the era of Frontier models?

[•Krishna @GenRevoeth]

@MayorDelMar This is the most comprehensive breakdown of how blockchain-based payments are going to have the greatest net-positive impact on the American SME.

[Syed, Mübarak Hussain @NeuroSeq]

We are excited to celebrate some outstanding science from our trainees today! Two of our undergraduate researchers, Nick & Mike, are presenting their Biochemistry honors theses. Zoe, our postbacc scholar, is presenting on the cell adhesion code of circuit wiring. Rewarding!