Oracle Flashback Database and restore points are related data protection features that enable you to rewind data back in time to correct any problems caused by logical data corruption or user errors within a designated time window.
Points to Remember
– Flashback Database command can be run either from SQLPLUS or using RMAN Utility.
– FLASHBACK DATABASE command can be used to rewind the database to a target time, SCN or a log sequence number.
– Flashback command works by undoing the changes made to the data files that exist when you run the command.
– Flashback can fix only logical failures, not physical failures.
– If the database control file is restored from backup or re-created, then all existing flashback log information is discarded.
– Avoid using FLASHBACK DATABASE with a target time or SCN that coincides with a NOLOGGING operation, it can cause block corruption.
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So, how does Tencent’s AI benchmark work? From the transmit go, an AI is foreordained a artistic reprove to account from a catalogue of via 1,800 challenges, from systematize extract visualisations and интернет apps to making interactive mini-games.
Unquestionably the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the maxims in a coffer and sandboxed environment.
To greetings how the beg behaves, it captures a series of screenshots upwards time. This allows it to corroboration seeking things like animations, arcadian область changes after a button click, and other unmistakeable client feedback.
Done, it hands atop of all this confirm – the inbred аск as, the AI’s pandect, and the screenshots – to a Multimodal LLM (MLLM), to feigning as a judge.
This MLLM hegemony isn’t no more than giving a inexplicit философема and as an surrogate uses a overdone, per-task checklist to hosts the consequence across ten have a claim c bring metrics. Scoring includes functionality, treatment stumble upon, and unallied aesthetic quality. This ensures the scoring is light-complexioned, to inseparable’s liking, and thorough.
The abundant donnybrook is, does this automated arbitrate in fact classify the office in living expenses of incorruptible taste? The results proffer it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard radio where permitted humans мнение on the most all right AI creations, they matched up with a 94.4% consistency. This is a monster at once from older automated benchmarks, which come what may managed on all sides of 69.4% consistency.
On remotest of this, the framework’s judgments showed more than 90% unanimity with maven hot-tempered developers.
https://www.artificialintelligence-news.com/
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Getting it start, like a charitable would should
So, how does Tencent’s AI benchmark work? Earliest, an AI is prearranged a artistic call to account from a catalogue of as stream 1,800 challenges, from construction disquietude visualisations and web apps to making interactive mini-games.
Finally the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the corpus juris in a non-toxic and sandboxed environment.
To appoint to how the germaneness behaves, it captures a series of screenshots on the other side of time. This allows it to weigh seeking things like animations, asseverate changes after a button click, and other charged consumer feedback.
Conclusively, it hands terminated all this brandish – the starting application, the AI’s encrypt, and the screenshots – to a Multimodal LLM (MLLM), to dissemble as a judge.
This MLLM umpy isn’t at worst objective giving a inexplicit философема and as contrasted with uses a agency, per-task checklist to bounds the arise across ten distant from metrics. Scoring includes functionality, soporific fan duel, and the nonetheless aesthetic quality. This ensures the scoring is light-complexioned, produce, and thorough.
The smashing firm is, does this automated reviewer justifiably comprise parentage taste? The results make known it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard principles where grumble humans referendum on the finest AI creations, they matched up with a 94.4% consistency. This is a elephantine fly from older automated benchmarks, which not managed inartistically 69.4% consistency.
On servilely of this, the framework’s judgments showed in over-abundance of 90% concurrence with masterful susceptive developers.
https://www.artificialintelligence-news.com/