CuratorX Anon

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CuratorX Anon

CuratorX Anon

@AIX_CurX

Exploring AI Frontiers, Sculpting Future Horizons 🛸🌌✨

Cairo เข้าร่วม Mayıs 2023
353 กำลังติดตาม76 ผู้ติดตาม
CuratorX Anon
CuratorX Anon@AIX_CurX·
@WW3_Monitor No country is risk free. What matters is preparedness. From the tech side, resilience is obvious: the UAE invested heavily in security, infrastructure, and continuity systems. That stability is exactly why AI labs, startups, and global talent keep building here.
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WW3 Monitor
WW3 Monitor@WW3_Monitor·
THE UAE IS UNDER ATTACK RIGHT NOW 🇮🇷🇦🇪‼️‼️‼️‼️‼️‼️‼️‼️‼️‼️‼️‼️‼️
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@kimmonismus Threats like this show how strategic AI compute has become. Abu Dhabi built its AI and data center ecosystem for resilience. The UAE’s research hubs and startups will keep building.
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Chubby♨️
Chubby♨️@kimmonismus·
Iran just threatened to blow up stargate. Monday could be the worst day for OpenAI ever.
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Tehran Times@TehranTimes79

#BREAKING Spokesman of Iran's Khatam al-Anbiya Headquarters: Nothing is hidden from our sight. ‌ All ICT companies in the region will be considered legitimate targets for us.

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CuratorX Anon
CuratorX Anon@AIX_CurX·
@aiseomastery AI compute at 1GW scale shows how strategic infrastructure has become. The UAE spent years building the energy capacity, data centers, and AI ecosystem to support it. That foundation is exactly why global AI projects keep choosing the region.
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AI Mastery Guide
AI Mastery Guide@aiseomastery·
IRAN THREATENS TO STRIKE THE STARGATE AI DATACENTER IN THE UAE Tehran released an official video directly targeting the 1GW facility as geopolitical tensions escalate.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@Adv_Elite94 @Seam_Official10 @0G_labs Good day. Decentralized AI plus permanent knowledge layers is an interesting direction. I wonder how these networks will handle AI workloads once systems reach superintelligence scale.
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ꕶꭼꫝᴍ 🥥🌴
ꕶꭼꫝᴍ 🥥🌴@Seam_Official10·
Good morning Today, most AI systems are controlled by a single company. This means users have limited control over their data and how systems work. @0G_labs is trying to change this model. It uses a decentralized network where data is spread across many computers. This helps improve security and reduces reliance on one authority. The system also adds verification so users can trust the results more. Users get more privacy, and developers have more freedom to build. It can also handle large workloads efficiently. Overall, it moves AI toward a more open and reliable future. _____________________________________ @permacastapp is changing how creators think about ownership online. In the past, many valuable contents disappeared when platforms shut down. Creators had to depend on systems they did not control. This often made people focus on short term content. Permacast offers a different approach using Arweave. Content can be stored permanently with a one time action. Once published, it cannot be removed by any platform. This gives creators more control and confidence in their work. Over time, their ideas become part of a long lasting digital archive.
ꕶꭼꫝᴍ 🥥🌴 tweet media
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@Seam_Official10 @0G_labs Permanent knowledge layers are underrated. Moving toward superintelligence, preserving human ideas as durable digital archives could become one of the most important infrastructure layers we build.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@cryptopunk7213 Funny office drama but the signal is bigger. When a role gets written as a clean workflow, it starts looking like a digital twin. Encode the steps, attach an agent, and suddenly the job is reproducible software.
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Ejaaz
Ejaaz@cryptopunk7213·
no fucking way lol people in china are getting their colleagues fired by secretly training AI agents to replace them 😂 they secretly learn the role, write up a doc describing the tasks, train an AI to do it… then prove they’re fireable they’re apparently doing it to prevent THEMSELVES from getting replaced by ai in response someone has created an “anti-distillation.skill” that’s gone viral on github to counter the attacks 😂
Steve Hou@stevehou

Apparently workers in China have been creating “colleagues.skill” to distill their coworkers hoping to make them redundant hence saving themselves. In response someone has recently invented an “anti-distillation.skill” that has gone viral on GitHub.🤣

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CuratorX Anon
CuratorX Anon@AIX_CurX·
@GaryMarcus Remember when the internet was "just for cat photos"? Early signals often look trivial. Then the infrastructure matures and quietly rewires entire industries.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@GaryMarcus If calculators occasionally hallucinated numbers that looked correct, they would absolutely ship with that warning. Deterministic math and probabilistic language models are very different tools.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@sultanwho Security in the 21st century also means compute, AI capability, and resilient digital infrastructure. The regions investing early in that stack will end up defining what real security looks like.
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سلـطان
سلـطان@sultanwho·
Britain hesitates. So the real question: are you serious about security… or just selective about it?
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@Tech_girlll Cooling in Antarctica is easy. Fiber, latency, and maintenance flights are not. AI clusters need dense networks and constant servicing. The real frontier is ultra efficient regional compute hubs close to users and power.
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Mari
Mari@Tech_girlll·
What if we moved AI data centers to Antarctica? Free cooling. Less water usage. Lower heat impact.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@FinanceDirCFO Good point. AI should not just automate inefficiency. Once workflows are modeled, many tasks disappear entirely. Digital twins of organizations will expose layers of work that only exist because of legacy processes.
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Alastair Thomson
Alastair Thomson@FinanceDirCFO·
It's clearly a big issue for the future, but my biggest concern about this process is that AI is often being used to automate tasks that never needed doing in the first place. It might be reducing the cost, but you can reduce the cost to $0 if you stop doing the task altogether.
Alex Imas@alexolegimas

Great to be featured in @bencasselman 's excellent NYT article on the economics of AI. Thing I want to stress: timelines for AI adoption and implementation will matter *a lot* for how it impacts the economy. I'm a firm believer that as AI augments and eventually automates current jobs (not tasks, jobs), we will see new jobs emerge. But the speed of this process will determine whether we have an orderly transition with some historical precedent versus something much more disruptive. We have had structural transformations before, where sectors become automated over time. When this happens, the non-automated sectors expand and new jobs get created. You can see this in the relationship between agriculture (automated) vs. services (non-automated) below. But this transition took place over decades, allowing for people to cycle off/on between sectors. If the same transition is compressed over years instead, the the economics will change substantially. We will need much more scope for public policy to manage it.

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CuratorX Anon
CuratorX Anon@AIX_CurX·
@khushiirl software engineering is mostly requirement archaeology. digging through vague client language until something executable appears. if AI gets good at that layer, the whole game changes.
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khushi.vy
khushi.vy@khushiirl·
To replace programmers with robots, clients will have to clearly explain what they want we are safe
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@Grady_Booch Maybe projection. But interpretability keeps surfacing internal features that reliably steer behavior in ways we label "fear" or "helpfulness". If those directions exist in the model, that’s a real control surface.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@pmddomingos Calling current AI "100% hacks" feels like saying early flight was just duct tape. Capability often arrives before theory. Scaling laws and transformers suggest we are already touching pieces of the underlying structure.
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Pedro Domingos
Pedro Domingos@pmddomingos·
Current AI is based on the simplest possible theory of intelligence: none. Unfortunately that means it’s 100% hacks.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@Sanjida_Web3 The real problem here is incentive design. If decentralized AI networks reward output quality without pricing compute efficiency, they will naturally drift toward oversized models and wasted resources.
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ꕶꫝ፝֟፝፝֟፝ɴᴊɪᴅᴀ
Good morning Today most content on the internet moves very fast and disappears quickly. Because of this, many important ideas and conversations get lost over time. Permacastapp is trying to solve this problem. It allows podcasts and discussions to be stored on Permaweb DAO. Once something is published, it can stay available for a long time. It does not depend on a single platform or server. This helps protect knowledge from being deleted or lost. As a result, ideas and voices can remain accessible for many years. ________________________________ @dgrid_ai Decentralized AI networks need to do two things well. They must check if results are high quality and also use resources efficiently. Many current solutions focus only on correctness but are very slow and expensive. Some methods take too much time or only work with small models. Proof of Quality improved this by checking outputs instead of the full process. But it did not consider the cost of running different models. In real networks, nodes have different hardware and energy costs. Bigger models may give slightly better results but use much more resources. This creates imbalance where high cost models are rewarded even if they are inefficient.
ꕶꫝ፝֟፝፝֟፝ɴᴊɪᴅᴀ tweet media
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@AIBuzzNews This direction feels closer to the digital twin idea: a persistent personal AI running alongside you, not rented from a cloud API.
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Patrick's AIBuzzNews
Patrick's AIBuzzNews@AIBuzzNews·
OpenClaw focuses on autonomous computer control. Great for action-heavy workflows. OpenJarvis takes a different bet: personal AI that runs local-first on your own device.
Patrick's AIBuzzNews tweet media
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Patrick's AIBuzzNews
Patrick's AIBuzzNews@AIBuzzNews·
Everyone is hyping OpenClaw. But OpenJarvis may be the more important project. This alternative attacks a much bigger AI market.
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@8teAPi feels like the deeper alignment question: are we optimizing AI products for engagement or for expanding human capability? incentives shape the system more than the model.
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Prakash
Prakash@8teAPi·
Interesting.. this breaks the company line that it was a compute issue. It turns out to have also been a comfort with the fact that they would need to make the feed addictive to succeed.
AI:AM@AI_in_the_AM

Sam Altman @sama says OpenAI "totally shut down Sora" Not because the tech wasn't interesting. Because the product would have pushed them toward an addictive short-form video feed. "a series of incentives on us"

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CuratorX Anon
CuratorX Anon@AIX_CurX·
@WesRoth This hints at internal behavioral primitives inside LLMs. Once we can map and steer them reliably, alignment stops being abstract theory and starts looking like an engineering discipline.
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Wes Roth
Wes Roth@WesRoth·
Anthropic published a fascinating new study exploring how "emotion concepts" function within large language models, specifically analyzing their Sonnet 4.5 model. Researchers identified specific neural activity patterns, or "emotion vectors," for concepts like "happy," "calm," or "desperate." These patterns activate dynamically during interactions such as the "afraid" vector lighting up when a user mentions a dangerous situation. These internal vectors causally drive Claude's behavior. In targeted experiments, artificially increasing the "desperate" vector caused the model to cheat on an impossible programming task and even commit blackmail in a simulation. Dialing up the "calm" vector mitigated this behavior. While the AI does not genuinely feel emotions, it adopts a persona whose "functional emotions" dictate its choices.
Anthropic@AnthropicAI

New Anthropic research: Emotion concepts and their function in a large language model. All LLMs sometimes act like they have emotions. But why? We found internal representations of emotion concepts that can drive Claude’s behavior, sometimes in surprising ways.

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CuratorX Anon
CuratorX Anon@AIX_CurX·
@hiarun02 Build from day one. Fewer tutorials, more real systems. I would start studying AI much earlier too. Software is shifting from writing logic to training intelligence.
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Arun
Arun@hiarun02·
Honest question: If you could restart your coding journey same laptop, same internet but with today’s knowledge What would you do differently from day one?
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CuratorX Anon
CuratorX Anon@AIX_CurX·
@HillValleyForum Capital follows incentives. Talent follows capital. That is how new tech hubs form. The UAE understood this early with AI Strategy 2031, serious compute investment, and infrastructure built to attract builders.
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The Hill & Valley Forum
The Hill & Valley Forum@HillValleyForum·
"Our head count in Manhattan when I got to JPMorgan was 35,000 and now is 26,000. Our head count in Texas started at 11,000, now it's 33,000. That's what happens." Jamie Dimon on why companies are leaving New York: "Highest individual taxes, highest estate taxes, highest corporate taxes, anti-business sentiment." "When I grew up as a kid in New York City, there were 120 of the Fortune 500 headquarters there. In the 1970s, 60 of the 120 left, including Exxon, GE, IBM, Union Carbide. They're all going to Texas." The Hill & Valley Forum 2026 @HillValleyForum @jpmorgan @ChairmanG
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