Trade $BABA (Alibaba Group) on Avantis with up to 10x leverage. Alibaba is China's largest tech conglomerate, operating the world's biggest e-commerce ecosystem. It also includes Alibaba Cloud (leading cloud provider in Asia), logistics, payments, and AI infra. Despite the stock being down 25% YTD, there is a major bull case. Alibaba has committed 50B USD to AI infra, its cloud business is growing 35% annually, and its homegrown AI models are competing at the frontier against DeepSeek. Could the tide turn for Alibaba?

India will always be humiliated by America and the reason is that we don't have any leverage. Kids of Netas and Babus are settled there, Americans will blackmail the shit out of both and will make them submit. Babus and Netas won't even think before selling the nation.

Always here showing love and support and hopefully my answer is right 🤝🫡 FUTURES REBASE LEVERAGE PERPETUAL CONTRACT

Karpathy said something you'll regret ignoring: "Remove yourself as the bottleneck. Maximize your leverage. Put in very few tokens, and a huge amount of stuff happens on your behalf." Loop engineering is the exact thing that does that. In a hand-run session, the operator handles two things: - deciding what the agent runs next - and checking its output before the next step Both are manual, and both decide how far the agent gets on its own without the operator. Loop engineering moves both steps into the system. A core operating structure surrounds the loop, and the diagram below depicts it. - A schedule decides what to run - Loop is the maker that produces the work - A separate checker agent grades the output - A file on disk holds the state they both read. The loop runs until either done, max iterations, or an exhausted budget. Here are some practical engineering considerations: 1) A model grading its own output justifies what it already did instead of catching where it failed. That's why a separate checker's findings return to the maker as the next instruction. And the cycle repeats until the checker finds nothing left to fix. 2) A loop with no stop condition burns tokens, and the cost climbs fast once sub-agents and long runs add up. That's why the exit must be set before the loop runs, not while it is running. A simple exit could be: ↳ fix only the major issues, run one final pass, and stop after two loops, with "all tests pass and lint clean" as the rule that ends it. 3) State has to live on disk, not in context. The model forgets everything between runs, so an MD file or a knowledge graph holds what is done and what is still open. Each run reads it and writes back to it, which lets a loop pick up again after days. 4) The lower the verification bar, the safer the loop. Boring, repetitive checks like a stale version string or a missing test are trivial to verify, so a loop runs them with little risk while the operator is away. Judgment-heavy work is loopable too, but only as far as the checker can confirm the result. Let's look at how an unattended loop fails in two ways. 1) It reports done when nothing is actually verified. The separate checker exists to prevent it, but it merges code faster than anyone reads it, so over weeks, the team stops understanding its own codebase while every check stays green. Green tests say the code passed the tests, not that anyone knows what shipped. Someone still has to read what the loop merges. 2) The checker keeps a running loop honest, but it only catches failures inside a run. The harness around the loop, like the prompts, tools, and checks wrapped around the model, still drifts and breaks in production as models change. That repair loop is usually run by hand based on observability traces. My co-founder wrote a detailed walkthrough (with code) on making that harness repair itself, where a failing trace gets diagnosed, the fix is verified against the exact input that failed, and the failure is locked as a regression test so it cannot recur. Read it below.

This is why, for example, when building with AI, it is recommended to leverage different models to evaluate the product.

🙃 💛 🫶 ⏰ Fresh strategy note 74: long games reward composure; keep one strong option open, because leverage rewards preparation

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FUTURES REBASE LEVERAGE PERPETUAL CONTRACT God bless @okx

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MY ANSWERS: FUTURES REBASE LEVERAGE PERPETUAL CONTRACT

Actually USA know that India govt. is deeply corrupt and USA have all the leverage now to make India a Vassal.State

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You cannot stop people from buying and selling as hard as they want. That is literally the market. Most of the time, the problem is not the chart. You don’t even buy spot anymore. You ape leverage because you want to get rich fast and flex like you are smarter than everyone else on X and TG Then it nukes. Now suddenly the same person who wanted casino upside starts crying for protection on X. This should not be allowed. This is manipulation.We got violated. But violent price action by itself is not a crime. You pressed the button. You chose the leverage. You chased the candle. You wanted the jackpot. If you cannot handle assets that can move violently both ways, don’t touch them. Go trade something slower. Because the market does not owe you a refund just because your greed entered before your brain did. $Siren $Skyai $Velvet $H and many more

💰 BITCOIN SALES KEY TO STRATEGY'S DIGITAL CREDIT MODEL, SAYS SAYLOR 💻 In a recent statement, Michael Saylor emphasized that Bitcoin sales are essential for supporting Strategy's burgeoning digital credit business. By using Bitcoin as a collateral asset, they aim to leverage price volatility to bolster their financial offerings 📈. This move highlights the evolving relationship between crypto assets and traditional financial services as institutional players seek innovative ways to integrate digital currencies into their operations. 📰 Source: CoinTelegraph Are digital credit services the next big frontier for Bitcoin adoption, or just a temporary trend? Let us know your thoughts. 👇

ROE measures how efficiently a company generates profit from shareholder equity. Here is how to use it 🧵 --- Formula: Net profit divided by shareholders' equity x 100. Example: NGN 5B profit. NGN 25B equity. ROE = 20%. NGN 20 profit per NGN 100 of equity. --- High ROE: Strong profit relative to equity. Management efficiency signal. Declining ROE: Profitability under pressure — or equity growing faster than earnings. --- Key rule: Compare within the same sector. Banks use higher leverage by design — their ROE is structurally different from consumer goods companies. --- ngnmarket.com This is for informational purposes only and not financial advice.

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