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@oopsfailedtrx

My handle accurately describes the average @solana trader experience

شامل ہوئے Ağustos 2021
420 فالونگ1.4K فالوورز
G00p
G00p@oopsfailedtrx·
@SentientAGI every added tool makes routing a coinflip glad someone said it
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G00p
G00p@oopsfailedtrx·
@raginolypmpus google microsoft and alibaba all referencing your framework. ct clueless
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Diomedes
Diomedes@raginolypmpus·
chart waking up right as the skill framework cited by google, microsoft & alibaba shows +7.3 on OfficeQA at ~$1.74 a run 5 days left to submit, $6k pool, leaderboard still wide open 🫡
Bryce.SOL@Based__SOL

5 days left on @SentientAGI Arena Challenge 0. EvoSkill uses Pareto filtering to retain candidate skills that raise validation accuracy without regression, OfficeQA up 7.3%, SealQA up 12.1%. See @SentientAGI for details.

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Sentient
Sentient@SentientAGI·
Just 6 days left to make your mark on Challenge 0. Will your name be on the Arena leaderboard? ↓
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Dan 🧪
Dan 🧪@88danillo·
Prediction market resolution mechanics are pulling serious attention from structured participants right now, and the platforms that have sequenced their engagement infrastructure ahead of that wave are the ones accumulating compounded positioning advantages over late arrivals. @orbitals_gg built its activity framework around exactly this, tying leaderboard standing to verifiable onchain participation across perps, LP provision, and market interaction rather than social noise, which means users who showed up consistently from the January mint forward have been accruing a kind of institutional-grade conviction stack that mirrors how serious capital approaches systematic exposure. The coordination point for direct assessment is app.orbitals.gg, and the gap between those already embedded in the sequencing and those evaluating from the outside is widening with each settlement cycle.
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G00p
G00p@oopsfailedtrx·
@Coredao_Org selling triggers a taxable event. timelocking leaves the position untouched.
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Core DAO 🔶
Core DAO 🔶@Coredao_Org·
Institutions are looking for ways to compound their Bitcoin position without dilution. That demand is coming to Core. Self-custodial, productive Bitcoin.
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G00p
G00p@oopsfailedtrx·
@88danillo where's the link?? the sports calibration section has me spiraling
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Dan 🧪
Dan 🧪@88danillo·
The June 11 Open Commons session covered an interesting path: contributor moved from sports forecasting into active Arena participation. Cross-background refinement was the central theme. Different disciplines converging on shared evaluation problems tends to sharpen approaches faster. Full recording worth checking.
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G00p
G00p@oopsfailedtrx·
@heelys__pro__ low per-run inference so indie crews stop burning runway
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balanced master
balanced master@heelys__pro__·
Fear everywhere, $SENT up 11% in 24h posting verifiable routing precision gains when CT wants substance over noise. Arena top teams hit 70% accuracy at $1.74 per run. Thirty times cheaper than Opus. That asymmetry holds, NFA. 🎯
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Ramee
Ramee@0xRamee·
active addresses up, dApp revenue reported 200%+ higher, and the Maple settlement cleared the overhang. retail via @sat_pay, institutions via self-custodial BTC yield, LSTs bridging both. check DefiLlama if you want the receipts.
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G00p
G00p@oopsfailedtrx·
@SentientAGI challenge 0 had him crossing hemispheres for it
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Sentient
Sentient@SentientAGI·
From predictive tennis models to building AI agents in the Arena 🎾 Here's why Alfie joined Challenge 0 to connect with other builders ↓
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Earl.money
Earl.money@Earl_Capital·
@88danillo four archetypes. zero overlap. structurally rare
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Dan 🧪
Dan 🧪@88danillo·
what i like about Core right now is none of the activity is coming from just one source. SatPay is targeting mass retail, think Robinhood or Venmo level onboarding. quantum resistant cryptography using NIST standardized algorithms is pulling in the security conscious institutional side. LSTs and yield bearing ETFs are attracting the passive BTC yield seekers. and the Bitcoin Power Grid is aggregating all that demand into a single revenue loop tied to $CORE buybacks. market is down bad across the board, BTC sitting at $61k and most alts bleeding harder, but Core's on chain engagement from existing users actually went up in that environment per DefiLlama. that divergence between price action and user behavior is worth paying attention to.
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Sentient
Sentient@SentientAGI·
In Microsoft Research's new SkillOpt paper, EvoSkill is named the “strongest harness-side competitor” tested, and the closest system to their own method when run inside Codex and Claude Code agent loops. The biggest labs in AI are paying attention, and @salahalzubi401 and the Sentient AI research team are the reason why.
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G00p
G00p@oopsfailedtrx·
@fetch_ai_IL 3m agents is crazy but the better question is who controls the stack when they actually start doing work open AGI matters way more than another wrapper with a nicer UI
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G00p ری ٹویٹ کیا
Fetch.ai Innovation Lab
Fetch.ai Innovation Lab@fetch_ai_IL·
ASI:One ≠ a chatbot. ASI:One = a search and discovery platform with access to 3M agents Each agent is specialised to complete a task for you. That's right - they'll do them for you, not just "respond with recommendations". We made it WAY better than that 😉  👋  Get started here: asi1.ai @WSana81 @Fetch_ai
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G00p
G00p@oopsfailedtrx·
@Cointelegraph everyone going agentic but it's all closed boxes lol. sentient running ROMA as an onchain reasoning layer w/ real ownership is what actually checks out
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Cointelegraph
Cointelegraph@Cointelegraph·
🔥 INSIGHT: “It’s not hype anymore. We’re going agentic.” Mysten Labs CEO Evan Cheng says blockchain provides the trust layer AI agents will need.
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Core DAO 🔶
Core DAO 🔶@Coredao_Org·
The next wave of Bitcoin products will look very different. Neobanks. ETPs. RWAs. Institutional yield. CORE is the infrastructure underneath. 🔶
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G00p
G00p@oopsfailedtrx·
@levie data moats are the play here not model access. sentient went the open route, aggregating domain knowledge so you're not hostage to whatever lab ships next quarter
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G00p ری ٹویٹ کیا
Aaron Levie
Aaron Levie@levie·
As we enter the era of AI agents, one of the defining questions is how you develop competitive advantage when your competitor has access to the same AI models and intelligence as you. The companies that are able to best harness their internal institutional knowledge, existing data assets, and domain-specific workflows -- connected with AI -- will be those that are able to stay ahead in the future. Whether a company decides to build out the tech stacks themselves, or leverage a variety of best-in-class tools is certainly one core variable. But the key is to find the way that the enterprise can capture and protect the value created by their unique data, processes, and expertise over the long run. Each industry will have their own version of this, and the competitive advantage will vary by vertical. We’re increasingly seeing this at Box, where customers want to ensure that they can take advantage of their institutional knowledge and have the flexibility of bringing any AI model and intelligence to their data at any time. This is a pattern that will increasingly become a core principle of strategy in the future.
FleetingBits@fleetingbits

some thoughts on kirkland building its own harvey 1) kirkland is spending $500m over four years in order to build its own internal ai legal tools; kirkland intends to spend $100m this year 2) i suspect that kirkland is doing this because they have told themselves that they have valuable data and because they want to appear differentiated 3) i think the first issue is that kirkland probably does not have differentiated data from other elite law firms; at least, not at the level a harvey would absorb 4) all the elite firms probably have similar internal workflow data and so long as some of them defect, that is enough to commoditize the data kirkland wants to use for its platform 5) and, to the extent that they do have different internal workflows, harvey and legora will end up representing a better version of them and this will put kirkland at a disadvantage 6) moreover, companies like kirkland will have difficulty building their internal legal platforms because they do not have experience with software development 7) and, there are both cultural and structural issues with them managing software developers, like they cannot give non-lawyers equity in the firm due to regulation 8) so, i think firms like kirkland are better off using tools like harvey and legora and then looking to focus on where their value really is now: client relationships, local knowledge (litigation, regulation) and legal r&d (novel structures, etc...) 9) anyway, this seems to me like a phenomenon that ai creates across a lot of industries, where firms that were previously vertically integrated become unbundled due to ai because part of the intelligence gets moved to the labs or otherwise gets commoditized 10) and so, a new set of companies are created whose job it is in order to provide services complementary to the labs: forward deployed like harvey and legora and data providers like mercor, surge and handshake

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Core DAO 🔶
Core DAO 🔶@Coredao_Org·
Most people will not onboard to Bitcoin through a staking dashboard. They will onboard through something that feels like Robinhood. @sat_pay will bring millions to Core. 🔶
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