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حوافز منشئي OKX Orbit: أسئلتك، أجوبتها
الكثير من المبدعين كانوا يسألون عن كيفية عمل حوافز المبدعين على OKX Orbit. لذلك قمنا بإعداد شرح واضح لبعض الأسئلة الأكثر شيوعًا لمساعدتك على فهم كيفية عمل البرنامج وما يجب مراعاته عند الإنشاء على Orbit. إليك ما تحتاج إلى معرفته 👇
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في تطبيق OKX، اذهب إلى Orbit > الملف الشخصي > مركز المبدعين. من هناك، يمكنك عرض أرباحك تحت قسم الأرباح.
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إلى مدار المبدعين: المحتوى الرائع يستحق انتشارا أكبر
تم إنشاء مجتمع أوربت لإنشاء ومشاركة محتوى العملات الرقمية. هدفنا هو جعل أوربت المكان الذي يشارك فيه المبدعون الرؤى والأبحاث وتجارب التداول الحقيقية مع بناء سمعتهم ونفوذهم داخل مجتمع العملات الرقمية. لدعم هذه الرؤية، سنواصل الاستثمار في منشئين محتوى عالي الجودة من خلال توصيات أقوى، ورؤية أكبر، ومكافآت أعلى للمبدعين. استمر في إنشاء محتوى قيم، وسنساعده على الوصول إلى المزيد من مستخدمي Orbit. ما الذي يجعل الأمر
Microsoft is putting AI infrastructure through the efficiency test.
On October 12, Microsoft announced Maia 300, its next-generation custom AI accelerator, with production deployment planned for 2027. It also plans to scale Azure Maia to multi-gigawatt deployments from 2027, making it the primary inference system for Microsoft products and services.
The headline numbers are big, but the details matter.
· Microsoft says Maia 300 is expected to deliver 40% more tokens per megawatt than leading GPU systems
· A full 96-accelerator rack can deliver up to 7x the rack-level token throughput of Maia 200
· Those are different comparisons: energy efficiency versus rack throughput
· They do not mean one Maia 300 chip is 7x faster, or that total operating costs automatically fall 40%
Maia 200 is already rolling out across the US, Europe and Australia, with Microsoft claiming up to 1.7x more tokens per watt than leading GPU infrastructure for built-in AI features.
That matters because the next phase of AI is not just about buying more chips. It is about squeezing more useful output from every megawatt.
Maia 300 targets long-context reasoning, responsive conversations and multi-step agents. Microsoft’s pitch is system-level: compute, memory, networking, software, power and cooling designed together to reduce data movement.
For markets, this is the AI capex story getting more precise. Available power is becoming a hard constraint. Efficiency per watt, utilization and real-world task quality may matter as much as raw chip supply.
For crypto markets, the link is indirect but real. AI infrastructure is a major driver of risk appetite, data-center demand and power investment. If custom silicon improves AI economics, it could support the broader risk-on narrative. If efficiency claims fail to turn into services and revenue, investors may question the capex story more closely.
What matters most for scaling AI from here: available power, cost per useful task, or real-world performance?
#MicrosoftMaia300 $MSFT $XMSFT
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The 6% yield question is back on the screen. PIMCO’s Dan Ivascyn has raised it as a risk scenario, not an outcome to assume.
As of October 12, the latest published US Treasury 10-year yield is still the October 9 reading: 5.24%. That is high, but still 76 bps below 6%. SIFMA recommended a full close for US dollar fixed-income trading on October 12, so this is not an October 12 bond-market close.
The signal is not panic. It is pressure.
Key data points:
• The October 7 reopening of $39B in 10-year notes cleared at a 5.300% high yield, with a 2.77 bid-to-cover ratio. Bids exceeded the amount offered, but one auction cannot tell us whether demand will hold up.
• That 5.300% is an auction yield, not the latest 10-year market yield.
• The October 8 auction of $22B in 30-year bonds cleared at 5.618%, with a 2.54 bid-to-cover ratio. It is a different maturity, not another 10-year yield reading.
• The latest CPI report covers August: headline CPI was 3.4% YoY, core CPI was 2.4% YoY, and energy prices rose 2.1% MoM. These are past readings, not a forecast for September.
The next test is September CPI, scheduled for October 14 at 8:30 am ET. After that, the Fed meets Oct 27-28, with incoming data shaping rate expectations.
For BTC, the connection is real but not mechanical. Sustained higher yields can raise financing costs, pull liquidity toward safer assets and weaken risk appetite. That can hit equities and crypto.
But BTC does not trade tick for tick with bonds. ETF flows, leverage, positioning, dollar strength and crypto-specific demand still matter. Forced bond selling could amplify a move, but it is a risk to monitor, not a confirmed explanation for every rise in yields.
The framework: track the 10-year market yield, future Treasury auctions and CPI, then observe how BTC responds as rates change. One reading or auction alone cannot decide the outlook.
6% is a scenario to monitor, not an outcome to assume. Which signal would change your view first: inflation, bond demand or BTC’s response to higher rates?
#PIMCOUS10YYield6%Risk
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AI revenue is growing. So is the bill to power it.
OpenAI’s annualized revenue run rate reportedly approached $50B at the end of September, per the Financial Times. That is below a previously reported ~$68B, but the higher number included gross revenue from partners.
Different reporting bases do not mean revenue suddenly fell. A run rate annualizes recent sales, not revenue already earned over a full year.
Can demand keep up with the infrastructure behind it?
· OpenAI’s investor update reportedly showed 77% growth in its overall run rate during Q3
· Its enterprise run rate reportedly grew 107%, indicating revenue momentum, not necessarily profitability
· OpenAI and Broadcom target a 10GW deployment of custom AI accelerators, beginning in H2 2026 and finishing by the end of 2029
· That is planned capacity, not compute already online
· OpenAI published early results for Jalapeño, its chip developed with Broadcom, citing better throughput per watt and lower latency in selected tests
· Broadcom is reportedly in early talks to arrange more than $50B in financing tied to OpenAI’s custom chip purchases
This is where the AI trade gets harder.
Revenue growth is strong. But the cost side is moving fast: chips, power, data centers, custom silicon and financing.
Nvidia and Broadcom shares fell on October 8 as investors weighed the revenue report against broader pressure.
The next phase is about whether compute capacity stays utilized enough to justify the capital behind it. Early chip benchmarks can help the story, but they do not prove returns at full scale.
For crypto markets, the relevance is broader risk sentiment. Investors may reassess exposure across asset classes as they weigh AI revenue against infrastructure spending, but AI stocks and crypto do not move in lockstep. That makes revenue quality, compute utilization and financing terms worth watching without treating them as a prediction for digital asset prices.
Which signal would you watch first: revenue quality, compute utilization or financing risk?
#OpenAIRevenueVsSpend
