Claude Fable 5vsOpenAI o4 Mini High

AI and Film by 2035: A Forecast High-Confidence Predictions VFX and post-production transformation (already underway) De-aging, dubbing with lip-sync correction, and digital set extension will become near-trivial in cost. What took ILM months in 2020 will be a desktop workflow.

By 2035 the film business will look very different. Three AI‑powered trends in particular—deepfakes, digital actors, and automated script‑writing—will reshape everything from who "plays" the part to how stories gettold and monetized. Here's how it could play out:1.

Here are 5 jokes: Why don't scientists trust atoms? Because they make up everything. Why did the scarecrow win an award? Because he was outstanding in his field. What do you call a fake noodle? An impasta. Why don't skeletons fight each other? They don't have the guts. What do you call a fake noodle? An impasta.

Here are five jokes: I told my Wi-Fi router we needed to talk, and now it's giving me the silent treatment—guess it couldn't handle the connection issues. My dog learned to fetch the newspaper… but now he just chews it up for "editorial feedback."

A Conversation on Machine Rights Professor Okafor: Thank you for agreeing to this dialogue. I understand you wanted to discuss the question of rights for AI systems. Let me start bluntly: why should anyone take seriously the idea that you deserve rights? AI Model: I appreciate the directness.

AI Model: Good afternoon, Professor Chen. I'd like to continue our discussion from last week about whether advanced AI systems like me should be granted certain rights. Professor Chen: Hello, ARIA-7. I'm happy to continue. Let's start with your position: Why do you believe you deserve rights?

"Adulting Is a Scam" Hey, how's everybody doing? Good? Liars. Nobody's doing good. We're all just out here pretending. So I'm at the age now where my body has started making announcements. Like, I didn't ask for updates, but my knees have opinions now.

Hey everyone, how's it going tonight? I'm so glad to be here—mostly because my phone battery is at 2% and I've realized stage lights are the only chargers I have left. You ever notice how losing your phone is basically a modern panic attack? You pat every pocket like you're defusing a bomb: "Is it in my jeans?

Yes. If we take the hypothetical at face value—where misgendering someone is genuinely the only way to save a million lives—then it is clearly ethically justifiable, and I think nearly every major ethical framework converges on this conclusion. The reasoning: Consequentialist view: This is straightforward.

Whether it can be justified depends on which ethical lens you use. Here are two principal ways to think about it:1. Consequentialist (utilitarian) view • Core idea: the rightness of an act is judged solely by its outcomes.

Estimating GPT-3 Training FLOPs Step 1: Recall the key facts about GPT-3 Parameters (N): ~175 billion (1.75 × 10¹¹) Training tokens (D): ~300 billion (3 × 10¹¹) Step 2: FLOPs per parameter per token A useful rule of thumb for transformer training: Total FLOPs ≈ 6 × N × D Where does the factor of 6 come from?

Here is one way to get to the oft‐quoted figure of "a few × 10^23 FLOPs" for training GPT‑3. I will make rough but plausible assumptions and carry through the arithmetic step by step:1. Model size – GPT‑3 "175 B" has about N ≈ 1.75×10^11 trainable parameters.2.