NVIDIA just released a smarter open-source AI for reasoning

Today, we’re going to talk about how Amazon’s Starfish AI is quietly rewriting the rules of e-commerce scraping the web, rewriting listings, and reshaping the way we shop. Also in the mix: Netflix uses AI in a big-budget sci-fi scene, NVIDIA releases reasoning-focused LLMs, and the AI-versus-artist debate keeps heating up.

In today’s post:

• Amazon’s AI takes over product listings

• Giveaway: Learn how to build AI agents for free in 3 hours course

• Netflix debuts its first generative AI scene

• NVIDIA launches compact reasoning LLMs

• 7 best AI agent builders for everyone

What’s Trending Today

Breakthrough

OpenReasoning-Nemotron shrinks 671B intelligence into efficient, usable models

NVIDIA has launched OpenReasoning-Nemotron a suite of distilled LLMs fine-tuned for reasoning. Built from DeepSeek R1 (671B), these smaller models aim to match brainpower with efficiency.

Here’s everything you need to know:

• The suite includes 1.5B, 7B, 14B, and 32B models—all distilled to retain reasoning capabilities from the 671B DeepSeek R1.

• Each version targets structured tasks in math, science, and code, not just raw text prediction.

• Despite smaller sizes, these models outperform peers in their weight class on logic-heavy benchmarks.

• The 32B variant hits near frontier-level scores in exams like AIME and HMMT, with or without GenSelect.

• Hugging Face hosts the full suite with open licenses, model cards, and plug-and-play inference support.

• Fine-tuning used curated datasets and chain-of-thought prompts to reinforce logic and symbolic reasoning.

• Use cases span math tutors, code assistants, scientific Q&A, and synthetic data generation.

Here’s what I think:

NVIDIA isn’t chasing bigger models they’re targeting smarter, more deployable ones. OpenReasoning-Nemotron shows that reasoning power doesn’t require frontier compute. It’s a strategic move that could shift how open-source LLMs compete with giants.

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Update

Netflix just aired its first AI-generated scene

Netflix has used generative AI in a TV show for the first time. The scene? A building collapsing in The Eternaut, an Argentine sci-fi series set in snowy Buenos Aires.

Here’s everything you need to know:

• Co-CEO Ted Sarandos said AI helped complete the sequence 10x faster and far cheaper than traditional VFX.

• It's the first time final generative AI footage has made it into a Netflix original series.

• Sarandos positioned AI as a way to democratize high-end effects for lower-budget productions.

• The move follows a 16% rise in Netflix revenue, boosted by global hits like Squid Game Season 3.

• But not everyone’s cheering—Hollywood unions have raised concerns about AI replacing creative labor.

• Tyler Perry even paused an $800M studio expansion over fears AI could undercut jobs.

• Animation pros say AI is becoming another tool in the artist’s kit—but insist humans still shape the final image.

Here’s what I think:

Netflix isn’t just experimenting with AI it’s normalizing it. For creators, this signals a shift: high-end visuals may no longer need high-end budgets. But the real question is who decides what gets automated and what remains human.

New Amazon project

Amazon’s new AI wants to rewrite how you shop

Amazon is quietly testing an AI system called Starfish a generative model built to rewrite the rules of e-commerce. Its goal? Automate and improve every product listing on the site.

Here’s everything you need to know:

• Starfish gathers product data from across the web then rewrites listings to be complete, consistent, and clear.

• Amazon expects it to add $7.5B in 2025 sales by improving product visibility and accuracy.

• The system draws from 200,000 brand websites and may power the new “Buy for Me” feature inside Amazon’s app.

• Sellers benefit from auto-generated titles, images, and bullet points freeing up time and reducing friction.

• For shoppers, it means faster decisions, especially for niche or hard-to-find products.

• But it also raises alarms: web scraping at scale blurs lines around ownership of brand data.

• As AI fills more catalog gaps, trust in what's "real" versus "machine-crafted" could become harder to untangle.

Amazon isn’t just building a better product page it’s building the infrastructure to control how product info is created and consumed online. That’s powerful. But anytime one company owns the source of truth, we have to ask: at what cost to transparency and competition?

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