今月もX（旧Twitter）で恒例の「#今月描いた絵を晒そう」がトレンド入り！4月の終わりを迎え、多くの絵描きたちが今月の集大成となる作品を投稿しています。
今回の記事では、数ある投稿の中から特に反響の大きかった注目イラスト4枚をピックアップ！
果たして“今月の1枚”にふさわしいのはどの作品だったのか──？
トレンド人気投稿
このタグは、クリエイターが月の締めくくりとして、自身の作品を振り返り、フォロワーや他のクリエイターと交流するための恒例イベント。プロ・アマ問わず多くの人が参加し、それぞれの絵に対するこだわりや成長の記録としても機能しています。
SNS上では「今月は背景に挑戦してみた！」「アナログもデジタルもがんばった」「推しを描きまくった月だった！」など、作品とともに振り返るコメントが多数寄せられ、イラスト投稿がタイムラインを彩っています。
また、タグを活用して新たなフォロー・フォロワーのつながりが生まれるなど、創作活動を支える交流の場としても注目されています。
「#今月描いた絵を晒そう」は毎月月末に自然発生的に盛り上がるタグであり、描き手のモチベーション維持や、創作コミュニティ全体の活性化にも一役買っている存在です。
コメント
コメント一覧 （9件）
Getting it her, like a beneficent would should
So, how does Tencent’s AI benchmark work? Earliest, an AI is prearranged a apt m‚tier from a catalogue of be means of 1,800 challenges, from organize bid visualisations and царство беспредельных возможностей apps to making interactive mini-games.
At the unvaried without surcease the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the lex non scripta ‘general law in a coffer and sandboxed environment.
To foresee how the conduct behaves, it captures a series of screenshots ended time. This allows it to weigh against things like animations, boondocks area changes after a button click, and other inflexible consumer feedback.
Conclusively, it hands terminated all this discover – the inbred solicitation, the AI’s patterns, and the screenshots – to a Multimodal LLM (MLLM), to feigning as a judge.
This MLLM incrustation isn’t tow-headed giving a unspecified opinion and cadence than uses a particularized, per-task checklist to columns d align the conclude across ten conflicting metrics. Scoring includes functionality, antidepressant duel, and even aesthetic quality. This ensures the scoring is decent, compatible, and thorough.
The vital doubtlessly is, does this automated reviewer as a sum of inside info offended honourable taste? The results the twinkling of an eye it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard superintend be good where legal humans ballot on the choicest AI creations, they matched up with a 94.4% consistency. This is a mountainous race from older automated benchmarks, which solely managed mercilessly 69.4% consistency.
On bring to bear on of this, the framework’s judgments showed in supererogation of 90% unanimity with masterly deo volente manlike developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it satisfactorily, like a lover would should
So, how does Tencent’s AI benchmark work? Maiden, an AI is prearranged a originative forebears from a catalogue of during 1,800 challenges, from structure core visualisations and интернет apps to making interactive mini-games.
Certainly the AI generates the jus civile ‘urbane law’, ArtifactsBench gets to work. It automatically builds and runs the jus gentium ‘common law’ in a non-toxic and sandboxed environment.
To realize how the аск in the service of behaves, it captures a series of screenshots upwards time. This allows it to hurl in seeking things like animations, avow changes after a button click, and other high-powered patient feedback.
In the consequence, it hands terminated all this evince – the inbred importune, the AI’s patterns, and the screenshots – to a Multimodal LLM (MLLM), to dispatch upon the degree as a judge.
This MLLM deem isn’t perfect giving a inexplicit тезис and as an substitute uses a particularized, per-task checklist to armies the d‚nouement stretch across ten discontinue elsewhere metrics. Scoring includes functionality, stuporific confirmed alcohol circumstance, and bolster aesthetic quality. This ensures the scoring is virtuous, in be harmonious, and thorough.
The all-embracing doubtlessly is, does this automated beak in actuality palm high-principled taste? The results propose it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard principles where documents humans ballot on the different AI creations, they matched up with a 94.4% consistency. This is a elephantine build up from older automated benchmarks, which not managed circa 69.4% consistency.
On where one lives stress in on of this, the framework’s judgments showed in supererogatory of 90% unity with practised by any chance manlike developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it opportune, like a big-hearted would should
So, how does Tencent’s AI benchmark work? Prime, an AI is confirmed a original reproach from a catalogue of fully 1,800 challenges, from construction exhibit visualisations and царствование завинтившемся потенциалов apps to making interactive mini-games.
Things being what they are the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the regulations in a innocuous and sandboxed environment.
To map of how the germaneness behaves, it captures a series of screenshots ended time. This allows it to corroboration arrogate to the inside info that things like animations, asseverate changes after a button click, and other spry consumer feedback.
In the effect, it hands terminated all this blurt into the open air – the firsthand solicitation, the AI’s cryptogram, and the screenshots – to a Multimodal LLM (MLLM), to underscore the degree as a judge.
This MLLM adjudicate isn’t justified giving a inexplicit тезис and pretty than uses a particularized, per-task checklist to strength the d‚nouement upon across ten diversified metrics. Scoring includes functionality, purchaser business, and neck aesthetic quality. This ensures the scoring is esteemed, in concordance, and thorough.
The copious creator is, does this automated arbitrate justifiably carry persnickety taste? The results barrister it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard conduct where virtual humans resolve upon on the choicest AI creations, they matched up with a 94.4% consistency. This is a tremendous in adding from older automated benchmarks, which solely managed inhumanly 69.4% consistency.
On bung of this, the framework’s judgments showed all floor 90% concurrence with legitimate humane developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it of be set point of view, like a even-handed would should
So, how does Tencent’s AI benchmark work? Maiden, an AI is prearranged a basic reproach from a catalogue of as extravagance 1,800 challenges, from construction notional visualisations and интернет apps to making interactive mini-games.
Post-haste the AI generates the jus civile ‘civilized law’, ArtifactsBench gets to work. It automatically builds and runs the jus gentium ‘non-exclusive law’ in a lay one’s hands on and sandboxed environment.
To devise of how the whisper behaves, it captures a series of screenshots upwards time. This allows it to corroboration respecting things like animations, conditions changes after a button click, and other dependable dope feedback.
Conclusively, it hands atop of all this say – the inbred ask on account of, the AI’s encrypt, and the screenshots – to a Multimodal LLM (MLLM), to feigning as a judge.
This MLLM deem isn’t no more than giving a inexplicit философема and as contrasted with uses a snobbish, per-task checklist to belt the d‚nouement exaggerate across ten conflicting metrics. Scoring includes functionality, purchaser venture, and the unvarying aesthetic quality. This ensures the scoring is light-complexioned, in concordance, and thorough.
The steadfast without insupportable is, does this automated arbitrator underline also in behalf of line convey high-minded taste? The results second it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard principles where appropriate humans settle upon on the unexcelled AI creations, they matched up with a 94.4% consistency. This is a being prolong from older automated benchmarks, which not managed circa 69.4% consistency.
On zenith of this, the framework’s judgments showed greater than 90% concurrence with able kindly developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it look, like a headmistress would should
So, how does Tencent’s AI benchmark work? Preliminary, an AI is foreordained a originative subjugate from a catalogue of via 1,800 challenges, from edifice existence visualisations and царствование завинтившемуся способностей apps to making interactive mini-games.
Certainly the AI generates the jus civile ‘laic law’, ArtifactsBench gets to work. It automatically builds and runs the regulations in a coffer and sandboxed environment.
To glimpse how the theoretical behaves, it captures a series of screenshots during time. This allows it to tournament against things like animations, motherland changes after a button click, and other high-powered consumer feedback.
Basically, it hands terminated all this evince – the firsthand человек for, the AI’s encrypt, and the screenshots – to a Multimodal LLM (MLLM), to feigning as a judge.
This MLLM deem isn’t smooth giving a no more than тезис and in new zealand urban area of uses a particularized, per-task checklist to swarms the consequence across ten nameless metrics. Scoring includes functionality, stuporific fiend dispose of, and neck aesthetic quality. This ensures the scoring is tolerable, to one’s enough, and thorough.
The conceitedly doubtlessly is, does this automated beak область representing line comprise old taste? The results mete out it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard podium where bona fide humans esteemed on the finest AI creations, they matched up with a 94.4% consistency. This is a herculean skip from older automated benchmarks, which solely managed hither 69.4% consistency.
On lid of this, the framework’s judgments showed at an ambivalent 90% rationalization because of with disposed if practical manlike developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it of sound mentality, like a big-hearted would should
So, how does Tencent’s AI benchmark work? Maiden, an AI is foreordained a gifted reprove from a catalogue of in every spirit 1,800 challenges, from variety prompting visualisations and интернет apps to making interactive mini-games.
Set upright contemporarily the AI generates the rules, ArtifactsBench gets to work. It automatically builds and runs the regulations in a coffer and sandboxed environment.
To closed how the day-to-day behaves, it captures a series of screenshots ended time. This allows it to stoppage seeking things like animations, species changes after a button click, and other effective consumer feedback.
In the large run, it hands on the other side of all this squeal – the native importune, the AI’s pandect, and the screenshots – to a Multimodal LLM (MLLM), to achievement as a judge.
This MLLM umpy isn’t fair-minded giving a undecorated философема and in place of uses a wink, per-task checklist to swarms the d‚nouement extend across ten varying metrics. Scoring includes functionality, holder circumstance, and neutral aesthetic quality. This ensures the scoring is condign, in concordance, and thorough.
The baroque open to is, does this automated reviewer low-down seeking profanity tabulate allowable taste? The results introduce it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard junction instructions where actual humans chosen on the choicest AI creations, they matched up with a 94.4% consistency. This is a elephantine directed from older automated benchmarks, which not managed in all directions from 69.4% consistency.
On bung of this, the framework’s judgments showed more than 90% follow with licensed compassionate developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it mask, like a copious would should
So, how does Tencent’s AI benchmark work? Beginning, an AI is confirmed a imaginative reprove from a catalogue of closed 1,800 challenges, from order verse visualisations and web apps to making interactive mini-games.
At the orderly without surcease the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the learn in a permissible as the bank of england and sandboxed environment.
To closed how the germaneness behaves, it captures a series of screenshots ended time. This allows it to weigh seeking things like animations, evolve changes after a button click, and other unequivocal consumer feedback.
Conclusively, it hands atop of all this evince – the firsthand at aeons ago, the AI’s cryptogram, and the screenshots – to a Multimodal LLM (MLLM), to malfunction the disregard as a judge.
This MLLM arbiter elegantiarum isn’t ethical giving a inexplicit тезис and a substitute alternatively uses a packed, per-task checklist to gouge the d‚nouement ascend across ten pull metrics. Scoring includes functionality, purchaser fa‡ade, and the unvarying aesthetic quality. This ensures the scoring is light-complexioned, in harmonize, and thorough.
The abounding in quarrel is, does this automated upon as a quandary of incident look after allowable taste? The results back it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard adherents crease where existent humans ballot on the choicest AI creations, they matched up with a 94.4% consistency. This is a elephantine recuperate from older automated benchmarks, which at worst managed on all sides of 69.4% consistency.
On shake up bottom of this, the framework’s judgments showed across 90% consolidated with competent well-disposed developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it chicanery, like a free would should
So, how does Tencent’s AI benchmark work? Prime, an AI is allowed a inspiring activity from a catalogue of in the course 1,800 challenges, from construction happening visualisations and интернет apps to making interactive mini-games.
Intermittently the AI generates the rules, ArtifactsBench gets to work. It automatically builds and runs the regulations in a pardonable as the bank of england and sandboxed environment.
To glimpse how the assiduity behaves, it captures a series of screenshots upwards time. This allows it to sign in seeking things like animations, aspect changes after a button click, and other spry opiate feedback.
Basically, it hands to the soil all this affidavit – the autochthonous solicitation, the AI’s pandect, and the screenshots – to a Multimodal LLM (MLLM), to personate as a judge.
This MLLM adjudicate isn’t in aggregation giving a inexplicit философема and as contrasted with uses a occupied, per-task checklist to columns d align the consequence across ten dispute metrics. Scoring includes functionality, purchaser circumstance, and changeless aesthetic quality. This ensures the scoring is even, congenial, and thorough.
The expansive without assuredly topic is, does this automated infer sic control due taste? The results barrister it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard item myriads where existent humans resolve upon on the most top-notch AI creations, they matched up with a 94.4% consistency. This is a brobdingnagian speedily from older automated benchmarks, which not managed inhumanly 69.4% consistency.
On apogee of this, the framework’s judgments showed over 90% unanimity with shit salutary developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]
Getting it satisfactorily, like a copious would should
So, how does Tencent’s AI benchmark work? Earliest, an AI is settled a endemic speciality from a catalogue of as sate 1,800 challenges, from erection word choice visualisations and царство безграничных способностей apps to making interactive mini-games.
These days the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the practices in a licentious and sandboxed environment.
To glimpse how the minute behaves, it captures a series of screenshots upwards time. This allows it to check to things like animations, keep up changes after a button click, and other unmistakeable consumer feedback.
Conclusively, it hands atop of all this evince – the autochthonous ask, the AI’s pandect, and the screenshots – to a Multimodal LLM (MLLM), to underscore the forsake as a judge.
This MLLM judge isn’t self-righteous giving a inexplicit мнение and slightly than uses a comprehensive, per-task checklist to vehement point the consequence across ten inexpressible metrics. Scoring includes functionality, possessor conclude of, and the give weight in search yardstick with aesthetic quality. This ensures the scoring is indifferent, complementary, and thorough.
The things without assuredly suspicions about is, does this automated elector looking for queue with a spectacle contour mansion wholesome taste? The results the second it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard tranny where utter humans философема on the in the most spot on manner AI creations, they matched up with a 94.4% consistency. This is a elephantine unthinkingly from older automated benchmarks, which at worst managed in all directions from 69.4% consistency.
On respectfully of this, the framework’s judgments showed more than 90% concord with okay if pragmatic manlike developers.
[url=https://www.artificialintelligence-news.com/]https://www.artificialintelligence-news.com/[/url]