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Your AI workforce across every app, every task, every day. Core infrastructure powering the global agent ecosystem. Builder of @HeySorinAI

Global
Joined July 2021
Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)Photo by Sahara AI πŸ”† (@SaharaAI)
What institutional trading desks have always had, now in the hands of every investor. Powered by @SaharaAI
Sorin is live. Your personal AI agent for global digital markets. Get started at HeySorin.AI
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Markets don’t reward you for seeing more data. They reward you for turning the right signal into action. That’s what @HeySorinAI is built for. Research the market, turn an idea into a strategy, backtest it, paper trade it, monitor live conditions, and move to execution β€” all in one workflow. If you haven’t tried Sorin yet, start here ↓ heysorin.ai/
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AI tutors should optimize for skills that survive their removal. Completed homework can hide outsourced reasoning. Hint design changes the practice; unaided transfer tests check whether the student can use what was learned. πŸ§΅πŸ‘‡
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A Turkey math study found an unaided exam penalty after generic chatbot access, largely mitigated by tutor safeguards. A Harvard physics trial found gains with a structured tutor. Different settings and short-term outcomes rule out a universal verdict.
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A tutor should require an attempt before a hint, then an explanation and a new problem solved unaided. Immediate learning, later retention and transfer need separate tests. An AI tutor succeeds when the student retains the skill without it.
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An alert can fire before you're ready to act. Switching pages, checking the signal again and rebuilding an order take time. The setup can change while you're doing it. In Sorin's Alpha Signals, click Place order on a monitor alert in Trigger History. Trading Copilot opens with the trigger context already attached. Sorin reruns the original conditions with current market data, then checks price drift and how much time has passed. If the signal no longer holds, it explains why and won't prepare an order you can submit. If the setup still holds, you get a prefilled order with the direction, leverage, margin mode and size carried over from your alert. Take profit and stop loss are editable. You decide whether to place it.
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A valid output type can still encode a wrong decision. Fast classifiers can make routing cheaper, provided their uncertainty is tested on the workload. Their value depends on which choices they can make and what happens when confidence fails. πŸ§΅πŸ‘‡
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A confidence score derived from output probabilities describes the model's distribution. Decision accuracy still needs testing on labeled workload data. Clustering and caching also affect latency, so a fast call cannot establish the performance of the whole pipeline.
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A tested threshold can route routine choices, with uncertain cases reviewed. Open-ended tasks still need generation; retrieval and fallback add costs. Authorization stays in code. Cheap inference earns automation only where decision errors are controlled.
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Sorin’s Alpha Signals now supports one-click order entry. Click Place order in a monitor alert to open Trading Copilot. Sorin rechecks the signal and prepares an order for your review if it’s still valid. Less time rebuilding an order after an alert fires. πŸ§΅πŸ‘‡
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If the signal still holds, review a pre-filled order with its direction, leverage, margin mode and size carried over. Adjust it and add take profit or stop loss before submitting. If it's stale, Sorin explains why and leaves no order you can submit.
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Open Alpha Signals in Sorin, then Trigger History. Choose Place order on a price alert to review it in Trading Copilot.
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Sahara AI πŸ”† retweeted
THE BOO CREW IS OUTπŸŽƒ SQUAD GHOULS ARE ROLLING IN!πŸ‘» Look who made it to the party: @SaharaAI @ValueQube_io @SPX_Finance #HalloweenParty #DeAgentAI #AIA
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Good to see you on this side of the market. 24/7 perps are coming to the US. The market stops waiting for you to wake up. No human watches a chart around the clock. A strategy does. Sorin builds yours from plain language and runs it on Hyperliquid. Backtested, paper-traded first, live from your own wallet.
I am excited to be an investor in trade(xyz) as they partner with ICE to bring 24/7 perpetual futures on Hyperliquid to the United States. As a market participant, I am looking forward to to using their innovative product to enhance my investment process.
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Robot evaluation must cover the whole workflow. A short demo leaves unanswered what happens when perception, control and recovery fail in sequence. Longer runs expose these failure points, guiding where better sensing and hardware tests may be needed. πŸ§΅πŸ‘‡
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A robot's planner and controller can each look strong in isolation while their errors compound across a task. Video may also omit contact information the task needs. For that failure, extra footage helps only if it carries the missing signal.
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Simulation needs its policy ranking checked against physical results. Hardware tests of changed scenes and recovery reveal where new data is needed. Completed work and the human effort behind it should decide deployment.
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An agent's identity cannot stand in for permission. Delegation needs limits and a way for the owner to take control back. Tracing a provider answers one question; controlling an action and recovering access require different mechanisms. πŸ§΅πŸ‘‡
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An ID can route an incident to a provider, and a log can record the action. Neither grants authority or restores access. A system that offers both can still leave the owner unable to stop the next action.
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Tools need to check scope before acting. Recovery must remain outside the agent's control, with revocation and handoff tested without unnecessary private data exposure. User control has to survive the agent's failure.
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