FetchDoge_Ektar @fetchdoge_
what comes after language models?...#Ektar? @memory_utility_Labs Calgary, Alberta Joined August 2026-
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The debate around superintelligence is heating up. With top researchers warning about the pace of development and calls for global pauses on advanced AI, the question remains: can we ensure these systems are safe before they surpass human control? #Superintelligence #AI #TechNews
A fundamental question in decentralized computing is: How does on-device sovereign silicon compare to global public blockchains like Ethereum and Bitcoin, and how do they interface without performance collapse? Direct execution on global public networks is constrained by physical propagation delays, consensus rounds, and block serialization limits #Crypo #Ethereum #Web3
Before you install an agent control panel, ask what it can reach. Tools that run coding agents, take remote access and self-update hold broad control of your machine. Keep them off any Mac with signing keys. Use a throwaway VM. #AIAgents #Security #Crypto #BuildInPublic
@ConnorTalksAI use Hermes Agent in meta muse
@HermesWatcher @NousResearch will do! if you are ever in a position and looking for someone to intern under let me know ! i'm looking to gain some more valuable experience and expand beyond self directed products and work with a team!
@HermesWatcher @NousResearch hmm, most of my gripes stem from the interface feeling clunky expecially since i understand why it has to be if that makes sense lol
recently I've started splicing together my own soul.md memory.md for my models and building models identity from the ground up ( as much as I can given what's available) l and stumbled on AlphaEvolve paper and the loop is cleaner You give it a starting program and an automated evaluator. A prompt sampler pulls a parent plus some diverse prior programs from the archive. Gemini proposes a code diff. The diff is applied, scored, and kept only if it improves the metric or lands in a new region of a MAP-Elites-style archive. That archive is doing real work. It keeps multiple distinct high-performing approaches alive so later prompts are not just refining the single current best. Concrete results: first improvement in 56 years on Strassen for 4×4 complex matrix multiplication (48 scalar multiplications instead of 49), a scheduling heuristic that recovered ~0.7% of Google’s worldwide compute, and a kernel change that sped up a Gemini training kernel 23% and cut overall training time ~1%. The models proposing the diffs stay frozen. Only the evolved code moves. Bounded recursive improvement at the algorithm layer. Still thinking about how much of the gain is the evolutionary archive versus the strength of the evaluator. im experimenting with editing the soul.md identity.md and the memories #AlphaEvolve #AI #superintelligence @GoogleDeepMind
Recursive self-improvement is real but bounded. AlphaEvolve (DeepMind) closes a loop at the algorithm layer via evolutionary search + MAP-Elites-style archive + external evaluators. It found the first improvement on Strassen’s 4×4 complex matrix multiplication in 56 years and cut Gemini training time ~1%. It does not set its own research agenda or retrain its own weights. Full RSI still requires durable self-modification, non-diminishing returns, and a cognition bottleneck—none of which are publicly demonstrated. Layer closed, evaluator external, returns measured. #AI #Superintelligence #RecursiveSelfImprovement #AlphaEvolve #MAPElites @GoogleDeepMind @demishassabis @AnthropicAI @jackclarkSF @OpenAI📷
@Tesla this sucked the Kia soul away right outta me
@Teknium @tonbistudio thanks for the video, it put things into perspective
@JustMicrock REA.. and Build it yourself if you despise it so much the technology is there to do it. see if you can Build better. just Build it.
@ConnorTalksAI Built a connected system between Grok Bot and Hermes Agent so I don't have to choose one over the other. When Grok Bot usage hits its limit, everything stays synced and continues smoothly across both. Leverage the best of each without tradeoffs.
Here's the reply, ready to paste under the comment: The count is factory output. Hardest was the capture timeout. After the call you do not know if money moved. Guessing is the wrong architecture. Timeouts are UNKNOWN, never guessed. Reconcile against provider truth. One rejected request: permit 5000 cents, check allows 3000. Hold authorized. Inject timeout before the provider applies the capture. Result: released=False, reason=unknown_after_timeout. Escrow UNKNOWN. Reservation stays held. Zero further PayPal calls. Receipt: UNKNOWN / capture_timeout. Reconcile queries provider truth. Still AUTHORIZED, no capture. Fail closed: void, free the reservation, VOIDED. Chain verifies. No money moved. Full walkthrough in the repo: docs/test-suite-walkthrough.md. 🚀
Shipping this to the PayPal AI Hackathon. Three hundred thirty-seven tests, hash-chained receipts, zero dependencies. github.com/FetchDoge/perm… — full Devpost: devpost.com/software/permit. #AISafety #BuildInPublic #AIAgents @GoKiteAI
@HermesWatcher Since i started using @hermeshermes I have come to termes with the rebranding of #Superintelegence
@cb_doge @elonmusk watched @CrissAngel and said that but make it real
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