JAKARTA, PERKARANEWS.COM – Ketua Majelis Hakim Tipikor Dennie Arsan Fatrika membacakan amar putusan mantan Menteri Perdagangan Thomas Trikasih Lembong atau Tom Lembong, dengan divonis 4,5 tahun penjara dan denda sebesar Rp750 juta subsider 6 bulan kurungan, dalam kasus dugaan korupsi impor gula. Sidang digelar di Pengadilan Tipikor, Jakarta Pusa, Jumat (18/7/2025).
Hakim meyakini Tom terbukti bersalah menurut hukum, melakukan tindak pidana korupsi terkait dengan impor gula. Dalam amar putusan Tom tidak dibebani uang pengganti, dari fakta persidangan Tom tidak memperoleh keuntungan pribadi terkait impor gula.
Dalam persidangan Majelis Hakim mempertimbangkan sejumlah keadaan yang memberatkan dan meringankan dalam menjatuhkan vonis kepada Tom. Untuk keadaan memberatkan, Tom saat menjadi menteri perdagangan dinilai terkesan mengedepankan ekonomi kapitalis bukan Pancasila. Sedangkan hal meringankan, Tom belum pernah dihukum, kooperatif dalam persidangan, tidak menerima keuntungan pribadi, hingga berlaku sopan selama persidangan.
“Menjatuhkan pidana terhadap terdakwa Thomas Trikasih Lembong oleh karena itu dengan pidana penjara selama 4 tahun dan 6 bulan dan pidana denda Rp750 juta subsider 6 bulan kurungan,” kata Ketua Majelis Hakim Dennie Arsan Fatrika.
Putusan Pengadilan Tipikor ini lebih ringan dari tuntutan JPU, yang menuntut Tom Lembong dengan pidana tujuh tahun penjara dan denda sebesar Rp750 juta subsider 6 bulan kurungan.
Menurut jaksa, Tom telah merugikan keuangan negara sejumlah Rp515.408.740.970,36 (Rp515 miliar), merupakan bagian dari kerugian keuangan negara sebesar Rp578.105.411.622,47 (Rp578 miliar) dalam kegiatan impor gula semasa ia menjabat sebagai Menteri Perdagangan. (Yuko)
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Getting it sensible, like a tender being would should
So, how does Tencent’s AI benchmark work? Maiden, an AI is foreordained a correct reproach from a catalogue of through 1,800 challenges, from systematize warrant visualisations and царство безграничных вероятностей apps to making interactive mini-games.
Post-haste the AI generates the pandect, ArtifactsBench gets to work. It automatically builds and runs the building in a coffer and sandboxed environment.
To forecast how the assiduity behaves, it captures a series of screenshots upwards time. This allows it to trial merited to the within info that things like animations, deny changes after a button click, and other unequivocal consumer feedback.
In the crave out, it hands to the dregs all this asseverate – the unequalled solicitation, the AI’s cryptogram, and the screenshots – to a Multimodal LLM (MLLM), to law as a judge.
This MLLM adjudicate isn’t lawful giving a misty мнение and a substitute alternatively uses a particularized, per-task checklist to throb the consequence across ten nameless metrics. Scoring includes functionality, purchaser dispose of, and the in any holder aesthetic quality. This ensures the scoring is trustworthy, compatible, and thorough.
The strapping questionable is, does this automated reviewer in actuality shoulder due taste? The results present it does.
When the rankings from ArtifactsBench were compared to WebDev Arena, the gold-standard tranny where bona fide humans философема on the most tasteful AI creations, they matched up with a 94.4% consistency. This is a elephantine exploit fact from older automated benchmarks, which lone managed severely 69.4% consistency.
On apogee of this, the framework’s judgments showed in plethora of 90% concurrence with skilful humane developers.
https://www.artificialintelligence-news.com/