Driving value through the @Oraichain ecosystem. AI x Web3.

Joined August 2024
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Today we're pleased to announce that Distilled AI has officially become a treasury company for the Oraichain ecosystem. This move solidifies our important position within the ecosystem and strengthens Oraichain's commitment to the convergence of AI and Web3. It also opens up avenues for more traditional and institutional investors to gain access and exposure to ORAI and its robust ecosystem. Distilled AI began as a project focused on confidential computing and knowledge distillation. We have great faith in the future of these technologies in the AI space, and they will remain central to our tech stack. Nevertheless, we want to be more closely integrated with the Oraichain ecosystem, and our new business model allows us to continue building while also reinvesting our revenue directly back into the ecosystem. Distilled AI will funnel all of its operating profits toward buybacks of ORAI, with the goal of eventually building up a treasury of ORAI. At the same time, we'll continue to innovate and build quality products that operate on the Oraichain network.
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Stop trading on feeling. Start trading on forensics. Let the math handle execution. Let your edge do the compounding.
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🔥 Oraichain Community Call Alert 🔥 🎙 We’re going live tomorrow on Oraichain’s X Space. Let’s talk AI, quant trading, what's next for Oraichain. ⏰ 13:00 UTC | 📍 @oraichain Feel free to bring your questions, ideas, and hot takes 😉 👥 Co-hosts: @tucq88, @regular__Joseph, @DucPham0212 🔔 Set your reminder & see you there!
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🎄 Holiday markets expose the truth about price traps. Noise looks like “signals,” and bored traders blow accounts. This is where AI and real tech earn their keep. Oraichain Quant Terminal already proves it. See it in action: quant.orai.io/

30 Dec 2025
🎄 Low volume, weak liquidity, turbulent price trap holiday markets. Noise dominates “signals”. Boring traders blow accounts, not markets. Oraichain Quant Terminal designed for chops. Disciplined traders get competitive advantage. Holiday “safe zone” configuration yields ~21% daily returns (up to 97% in extremes). | SL 0.3-0.5% | TP 1.0-2.5% | Vol 0.7-1.0 | 3-5 signals The top-performing setup (up to 37.5% daily): Vol 1.0 | 5 signals | SL 0.5% | TP 2.5% It works because: In weak liquidity, tight stops are sought, sub-1% scalps cause fee churn, and volatility filters await meaningful swings. More signals = clearer range edges ⚠️ Holiday markets reward discipline, not financial advice.
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26 Dec 2025
Manual trading is the slowest part of your strategy. Not another bot, but a control panel to build your own trading agents & trade across DEXs from one terminal. Build agents, manage positions, and control TP/SL - all in Oraichain Quant Terminal. You set the rules and risk. The agent executes using quant models - to find entries, select orders, and run 24/7. Miss fewer moves. Think less. Execute better. 👉 quant.orai.io
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Clear proof that data and AI have crossed the line from demos to real systems that print outcomes!
24 Dec 2025
Remember the Dec 19 $BTC crash? They panicked. We shorted. While the market bled, Oraichain Quant Terminal (Top10 assets model) signaled the drop early. During the extreme volatility zone, total system PnL delivered $189.11 in profit per $1 of risk. Here’s how it worked 👇🧵
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23 Dec 2025

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19 Dec 2025

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The AI cost–performance curve is still breaking downward. Performance (GPQA) keeps climbing toward PhD-level reasoning, while cost per million tokens collapses on a log scale. When cost drops as capability rises, AI stops being a demo tool and becomes deployable infrastructure. While most are still talking about AI, Oraichain Quant Terminal (quant.orai.io) is already executing AI-driven, agentic trading on decentralized venues, and the window for manual-only trading is quietly closing. 👉 Try quant.orai.io and see the proof in execution.

17 Dec 2025
No signs of an end to rapid gains in AI ability at ever-decreasing costs (which is a log scale) yet. I have to update this monthly or more frequently at this point. All AI benchmarks are flawed, but GPQA Diamond has been a pretty good one, though likely close to being maxed out.
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11 Dec 2025

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11 Dec 2025

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Are you preparing for new skills and roles? 📊 Negotiation, problem-solving, and leadership will matter even more in the near future because they become your edge when your teammates are autonomous agents running at machine speed. → Step up and become the ones who lead the way; directing, deploying, and productizing our agent teammates. ↳ Discover the way now at Thesis.io — an agentic workspace with real-time data streams and customizable workflows. 🚀
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5 Dec 2025

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📊 @AnthropicAI dropped fresh research using 100,000 real Claude conversations shows just how aggressively AI is compressing work: • Tasks that normally take ~90 minutes now shrink by ~80% with AI assistance, with a median time saved of 84%. • Time savings vary widely depending on task complexity, human expertise, and how structured the information is (diagnostic image checks: 20% vs. information compilation: 95%). • Contrary to popular belief, AI doesn’t hit low-wage jobs first; higher-wage knowledge tasks see the greatest acceleration because they’re longer and more text-heavy. • If today’s AI capabilities were fully adopted across the economy over 10 years, U.S. labor productivity could nearly double long-term growth rates, on par with the post-war boom and the late-1990s tech surge. → The data is clear: the next wave of productivity belongs to people who can compress work with AI. Build AI Agents, automate your workflows, and turn ideas into leverage with Thesis.io — your vault for real AI advantage. 🚀

25 Nov 2025
Replying to @AnthropicAI
Based on Claude’s estimates, the tasks in our sample would take on average about 90 minutes to complete without AI assistance—and Claude speeds up individual tasks by about 80%. The results varied widely by profession:
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Without AI, the US would be in a recession.
The US economy is now BUILT on AI: US private nonresidential fixed real investment in data centers has soared 300% over the last 3 years. During the same period, inflation-adjusted nonresidential investment in structures excluding data centers has barely seen any growth. These are offices, shopping centers, hotels, warehouses, factories, manufacturing facilities, and other commercial buildings. Meanwhile, AI-related spending has contributed 62.5%, or 1 percentage point, to the 1.6% US GDP growth in the first 6 months of 2025. Without AI, the US would be in a recession.
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📊 AI Macro Reality Check If you only looked at headlines, you’d think the AI bubble debate is the whole story, but the real picture comes from the data, and it shows why the narrative is far more complex than “AI overheating.” The chart captures the central tension of the current AI economy: ▸ Industry Strain at 8.6 is the only true danger zone, reflecting unprecedented capex commitments (like OpenAI’s $1.4T), while accelerating hyperscaler spend, rising debt, and nonstop data-center reinvestment show the buildout is running hotter every quarter. ▸ Revenue Momentum is the strongest counter-argument to the bubble thesis. Revenue doubling every 0.8 years (~9.6 months) is the opposite of a speculative bubble; hyper-growth demand is real and accelerating, not imaginary. ▸ The “Worsening” labels on the yellow gauges (Valuation and Funding) come primarily from macro-economic pressure, not AI fundamentals. → As of late November 2025, the market still sits in a technical “Boom” phase, with only 1 out of 5 critical gauges flashing red. The ecosystem is stressed but functional and as long as Revenue Momentum stays ahead of Industry Strain, the fundamentals support the price action. The real risk isn’t the technology; it’s the financing structure required to sustain it.
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20 Nov 2025

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While most still assume that ‘the best model wins,’ the market is showing otherwise 👇 ▸ Products actually succeed when they deliver compounding user value, raw model strength alone doesn’t cut it. ▸ Once a product finds PMF, smart teams begin building their own specialized models backed by unique data and RL environments. Starting from open-base models, they fine-tune for real workflow advantage. And that’s exactly where Thesis.io fits in — an agentic workspace with real-time data streams and customizable workflows. If you believe the future belongs to AI products with their own intelligence engines, you’re early! ↳ Ready to productize your ideas? Discover it now at Thesis.io 🚀

13 Nov 2025
Cursor is almost certainly the fastest company in history to reach $1B in ARR. GPT-5.1 did research and generated the following graph to show how long it took these companies to go from founding to $1B ARR.
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15 Nov 2025
🤖 Blockchain oracles are evolving. Our AI oracle links AI to the world, and the world to Web3 - enabling data verification, reasoning, and automation across decentralized systems. This is the infrastructure layer of intelligent Web3.
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📊The data proves it again: AI rewards agility. The more flexible your workflows, the higher your return.
MCKINSEY JUST DROPPED THEIR 2025 AI REPORT. HERE’S THE TLDR: 1/ 90% of companies “use AI,” but 67% are still stuck in pilot mode. Corporate AI theater is alive and well lol. 2/ 62% of orgs are experimenting with AI agents, 23% are scaling AI agents. Most are in tech and healthcare. 3/ The impact gap is massive. 64% say AI helps innovation, but only 39% see real EBIT gains. 4/ The high performers (top 6%) think bigger. They rebuild workflows, set growth goals, and invest real budgets not just POCs. 5/ Leaders who own AI personally are 3x more likely to scale it. Makes sense. 6/ The winners use AI to transform how work gets done, not just speed it up. 7/ The average company measures efficiency. The best ones measure how fast their agents can act. 8/ Risk management is catching up with 51% have already seen AI backfire, mostly from inaccuracy. 9/ The workforce impact is foggy. 32% expect cuts, 13% expect growth, everyone else is guessing. 10/ AI adoption is mainstream, but true transformation hasn’t started. Early days.
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