Thomas Laverne

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Thomas Laverne

Thomas Laverne

@thomas_laverne

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Montpellier, France Katılım Eylül 2010
1.2K Takip Edilen550 Takipçiler
SULLY 🎨
SULLY 🎨@artofsully·
been replaying Halo Wars over the weekend and using it as a good case study for making an RTS camera that can smoothly navigate rugged elevation using an adjustable + simplified proxy grid! #gamedev #madewithunity
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McMeddon🌻
McMeddon🌻@McMeddon·
found another S tier screenshot in my library Must been the 2025 advent map 17
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みょん@ひつじ
建築開始から35日目の進捗 残り建築予定 ・民家2軒 ・お寺(黒羊毛の場所) ・小学校の周辺装飾 ・空いてるところの装飾 ・共有(繁茂、モダン)に1軒ずつ 残り4週間! がんばるぞ~(`・ω・´) #夜空の夏
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柚子
柚子@justinia_mc·
海辺の村から少し離れた海岸に別の港町を作り始めました。 海辺の村が漁村だとしたら、今度の港はもう少し貿易もできる港という感じ。 水深の深い入り江を生かして大きめの船も接岸できる港と、崖上にちょっとした商業の町を作る予定。 島の産品を積み出しする港町。 #Minecraft #MiniaTuria
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Senny
Senny@SennySupreme·
@thomas_laverne Looking good! You could add some trees and shubbery to really bring it together, depending on the setting of your game, maybe some ruined fortifications?
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Gavel
Gavel@GavelGamer·
Still the best floating continent theme
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Thomas Laverne
Thomas Laverne@thomas_laverne·
@McMeddon It's beautiful ❤️! Would you have pointers that would help me to understand how to generate such terrains, I'd like to know more!
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McMeddon🌻
McMeddon🌻@McMeddon·
Mesa + Snow i like c:
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Pierre-Louis Biojout (PLB)
A CS professor at the top engineering schools in Europe just told my sister that AI is bad and people shouldn’t use it, especially to code. This is 2026. He teaches at Polytechnique (l’X). He runs the exact same CS course I took six years ago. Nothing has changed in his syllabus and nothing has changed in his head either. It is the intellectual equivalent of a physics professor teaching that the earth is flat, and the institution tolerates it. Here is the irony though. My sister is getting a vastly better education than I ever did, because on top of the lectures she now has a 140 IQ tutor that answers every question, generates infinite examples, and reviews her code at 2am: Claude. For any student with even a small amount of agency, this is the most extraordinary moment to be learning anything. Grow. Build. Keep shipping nanojunior.
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Thomas Laverne
Thomas Laverne@thomas_laverne·
@rizbicki Oui moi même j'ai fait le chemin a l'envers. Bye bye overleaf
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Rafael Izbicki
Rafael Izbicki@rizbicki·
A student recently told me: "Apparently, you can now use LaTeX locally on your computer. We don't need Overleaf anymore." The old becomes new again, helped along by Overleaf becoming really slow.
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Thomas Laverne
Thomas Laverne@thomas_laverne·
@Briviagra Comme je vous comprends, et pourtant j'ai encore espoir que ça change
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Fabien
Fabien@Fabien_Mikol·
Luc Julia: les modèles généralistes ne servent à rien, l'avenir est aux modèles spécifiques @spolu: il est devenu inutile de fine-tuner les modèles sur des tâches spécifiques, mieux vaut donner directement des outils aux modèles généralistes, ça suffit, ça fonctionne aussi bien !
Fabien@Fabien_Mikol

Pour défendre la pertinence des LLM généralistes (critiqués par les 2 autres invités), @SamuelFitouss10 mentionne leur utilisation par @IsomorphicLabs. Luc Julia dénonce une "confusion énorme"... en confondant lui-même "agentique" et "spécifique", puis le fine-tuning avec le RAG.

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Ryan Hart
Ryan Hart@thisdudelikesAI·
A Oxford PhD student got flagged for submitting AI-generated work. His advisor called it the most sophisticated research process he had seen in 20 years. The student had not used AI to write a single word. Here is the workflow that got him reported. He starts every essay with a diagnostic he calls brutal. He dumps his rough argument into Claude and asks one question: what are the three weakest logical jumps in this reasoning, and where would a hostile examiner attack first? The AI does not write his essay. It destroys his draft, and then he rebuilds from whatever survives. Most students using AI are doing the opposite. They hand Claude a topic and ask it to write. He hands Claude his thinking and asks it to find every place where that thinking falls apart. The difference between those two approaches is the difference between outsourcing your brain and sharpening it. The second step is the one that made his advisor go quiet. He uploads the five most important papers in his field alongside his draft and asks Claude what claims in his argument contradict or oversimplify what these authors actually found. Most PhD students cite papers they have skimmed once. He cites papers he has been forced to genuinely reckon with, because Claude keeps catching the places where he got them wrong. The final move is almost unfair. Before he submits anything, he pastes his conclusion and runs one more prompt. He asks what a philosopher of science would say is missing from this argument and what assumptions he is making that he has not defended. His essays come back from reviewers with phrases like unusually rigorous and demonstrates rare critical depth, and his committee has no idea that the depth came from a machine asking him harder questions than any human in his department was willing to ask. The academic integrity hearing lasted three hours. The panel asked him to rebuild his methodology from scratch in the room. He opened his laptop and showed them exactly how the workflow ran, prompt by prompt. They did not just clear him. They gave him the highest grade in the department's history and asked him to present the process to faculty. Here is what that story actually means. What took most PhD candidates six months of back-and-forth with advisors, he was compressing into a single session because he had figured out something almost nobody else has. AI does not make your thinking better by replacing it. It makes your thinking better by attacking it faster than any human critic ever would. He was not using AI to write. He was using it to think harder than he could alone. The tool is the same one everyone has. The workflow is the part nobody is teaching.
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