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Mortal Shell II Beta - Native TSR vs DLSS Performance. Improved image quality and nearly 80% performance increase when using DLSS Performance! DLSS FTW 😀

Jacob Freeman

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37,918 views • 1 month ago •via X (Twitter)

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And how about DLSS off vs DLSS 4? Better image quality and of course much faster performance! 👀

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Hair detail and rendering look quite a bit better with DLSS 4.5 in Stellar Blade. 4K DLSS Performance 👍

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It looks like the game only renders correctly when DLSS is enabled and the internal resolution is below 1080p. Above that threshold, a lighting pass is missing. This explains why DLSS doesn’t perform as expected at 1440p or lower, since performance is impacted by the extra lighting pass. It also matches why Digital Foundry saw a bigger boost, since they tested DLSS at 4K. and It explains why DLAA looks worse than DLSS Quality at 1440p or below. Big thanks to ハイ／🌼 and yeradd for the info.

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OpenClaw setup made me $23,472 Literally overnight my $100 turned into $2,411 Average bot win rate 71% Copytrade: Here is the full strategy: The system builds automated workflows for trading by turning domain expertise into structured skills that activate automatically when specific market conditions appear Skill architecture Each skill is a modular package that includes instruction scripts and reference data This allows the system to apply specialized workflows without needing manual input for every trade Progressive context loading Skills use a three layer structure Only minimal metadata loads at first Full instructions historical data and supporting resources load only when required This reduces resource usage while keeping advanced trading capability Trigger detection Skills activate automatically when market conditions match predefined triggers such as volatility levels orderflow behavior or news sentiment This ensures the right workflow is used at the right time without manual action Workflow execution Once activated each skill runs a predefined multi step process including Real time price tracking and order book analysis Factor generation and backtesting Signal aggregation from machine learning models news sentiment and orderflow Risk assessment and capital allocation Trade execution with retries and position splitting Consistency and reliability All workflows are embedded directly into the system which ensures consistent execution instead of random decision making Every factor signal and risk rule is applied in a structured way Testing and iteration Skills are continuously improved using historical backtesting simulated trading and live performance tracking to maintain reliability in real market conditions Automation edge Instead of creating new strategies every time the system repeatedly uses optimized workflows This reduces complexity increases consistency and scales performance across thousands of trades Performance snapshot Started one month ago with $500 Current daily profit $2,300 per day Morning profit today $71,452 The system runs fully autonomously constantly scanning markets generating signals auditing trades managing risk and executing orders to maximize compounding returns

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winkle.

44,158 views • 4 months ago