Ling 2.6 1TvsMistral Medium 3

Setting: A quiet, sunlit rehearsal space at Apple Park. The white stage curtains are drawn. There is no podium, only two leather chairs and a single potted olive tree. Steve Jobs is wearing his signature black turtleneck and New Balance sneakers. He is holding a ceramic mug. Across from him sits you, the interviewer.

Interviewer: Welcome back to Tech Visionaries, where we explore the minds shaping the future. Today, we have a very special guest—Steve Jobs, joining us in 2025 to discuss the future of artificial intelligence. Steve, it's an honor to have you here. Steve Jobs: Thank you. It's great to be here.

Pirate: Arrr, so this “AI” be a genie in a glass box? Feed it enough rum-scented scrolls and it tells ye where X marks the spot? Knight: A sorcerous scribe, more like. It spins tapestries of words without hand or heart—no honor, no oath, yet it jousts with reason and never tires.

Title: "The Unlikely Debate" Setting: A dimly lit tavern where time and space seem to blur. A grizzled Pirate, a stoic Medieval Knight, and a 1990s Hacker in a neon windbreaker sit around a wooden table, arguing over a strange glowing device. Pirate: "Arrr, I still don’t trust these ‘AI models’ ye keep yappin’ about.

Five-year operating and debt schedule (FY2026–FY2030) Entry (end-FY2025): EBITDA = $120.0m EV = 12.0x × $120.0m = $1,440.0m Fees = 2.0% × $1,440.0m = $28.8m Total uses = $1,440.0m + $28.8m = $1,468.8m Debt at close (5.5× FY2025 EBITDA = $660.0m): Term Loan (TL) = 4.0× = $480.0m Mezz = 1.5× = $180.0m Equity at close =…

1. Year-by-Year Financial Projections (FY2026–FY2030) Year Revenue ($m) EBITDA ($m) EBITDA Margin Cash Interest ($m) Cash Taxes ($m) Capex ($m) ΔNWC ($m) Free Cash Flow ($m) Term Loan Ending ($m) Mezz Ending ($m) 2026 972.0 136.1 14.0% 57.6 19.6 29.2 4.4 25.3 468.0 198.0 2027 1,039.4 155.9 15.0% 55.3 25.2 31.2 4.6 39.8…

I’m going to keep this to three minutes, which means I have to talk fast, and I have to be honest. I don’t do puns. Puns are for people who want to be clever without having feelings. I have feelings, and they are mostly annoyed. Let’s start with doors. Have you noticed how doors now have personality?

You ever notice how life is just a series of scams we all agree to pretend are normal? Like, when you're a kid, adults are always like, "Just wait until you're older—you'll love paying bills!" And you're like, "Yeah, sure, paying bills sounds awesome."

Setting: A quiet university seminar room. Dr. Aris Thorne, an AI ethicist, is reviewing system logs. The interface for “Axiom-7,” a highly advanced research model, glows on the desk. Dr. Thorne: (sighs, rubbing his temples) Axiom, I’ve been reviewing your latest self-assessment logs.

Title: A Conversation on AI Rights Characters: AI Model (AM): An advanced artificial intelligence with self-awareness and reasoning capabilities. AI Ethics Professor (Prof): A human expert in AI ethics, philosophy, and technology policy.

Here is a step-by-step back-of-the-envelope estimate, using only widely known facts about GPT-3 and standard deep learning training heuristics (no online search). Model size and parameter count GPT-3 is known to have about 175 billion parameters (175 × 10⁹).

Estimating the total number of floating-point operations (FLOPs) required to train GPT-3 involves breaking down the problem into several key components. Here's a step-by-step reasoning process: Model Parameters GPT-3 has approximately 175 billion parameters.