DeepSeek R2 is coming and its going to shake the world

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In today’s post:

• DeepSeek: R2 launch (incoming)

• Meta Llama 4: 3 new models :)

• Microsoft: Quake II

• Trending AI tools + Giveaway

What’s Trending Today

DeepSeek

DeepSeek R1 rivaled the best models from the US. Now R2 is coming.

The last time a Chinese AI model made this much noise, it was DeepSeek-R1. And guess what? It didn’t just compete it rivaled the best models from the US.

• R1 shocked the tech world by matching top-tier performance without the massive costs.

• It wasn’t just hype the model delivered strong reasoning, fast responses, and serious efficiency.

• All of this from a company barely two years old, backed by hedge fund money and skipping the flashy marketing.

Now? The next version DeepSeek-R2 could be just weeks away.

Here’s what we know (and what’s coming):

• DeepSeek teamed up with Tsinghua University to improve how AI thinks.

• They combined Generative Reward Modeling (AI learns from what humans prefer) with Self-Principled Critique Tuning (AI corrects itself before giving you a bad answer).

• The result? A model that’s faster, sharper, and more human-like.

• This new tech is called DeepSeek-GRM and it already beats older systems in tests.

• And yeah, DeepSeek might open-source it soon.

All of this is likely going into R2.

If R1 was their “proof-of-concept,” R2 could be their global flex.

Here’s what I think:

We’re not just watching another model release. We’re watching China close the AI gap with the US not by copying, but by innovating. If R2 lands as expected, it won’t just shake up the leaderboard it could change how AI shows up in classrooms, startups, and every chat window on Earth.

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Meta

Llama 4 Is Meta’s Play for the AI Endgame

Meta didn’t wait for a fancy launch event. They rolled out Llama 4 on a Saturday like it was no big deal. But it is.

There are three models: Scout, Maverick, and Behemoth. Each one trained on mountains of text, images, and video to “understand the world” better. And they’re big. Like, really big.

• Maverick: 400B total parameters. Beats GPT-4o and Gemini 2.0 on key benchmarks (but still trails Gemini 2.5 Pro).

• Scout: Built for huge documents — it can handle 10 million tokens in one go and runs on a single H100 GPU.

• Behemoth (still training): Nearly 2 trillion parameters. Internal tests show it outperforms GPT-4.5, Claude 3.7, and Gemini 2.0 Pro on math and STEM tasks.

These models use a Mixture of Experts (MoE) setup only some parts activate at once, making them faster and cheaper to run.

But there’s drama:

• EU developers? Blocked. Meta’s license bans them, likely due to local laws.

• Big platforms? Need a special license if they’ve got 700M+ users.

• And politically? Llama 4 is less cautious. It now answers more “controversial” prompts that older versions dodged.

Here’s what I think:

Meta isn’t just building models — they’re building a counterweight. If OpenAI, Google, and Anthropic are playing chess, Meta just kicked the board and threw in a 2 trillion parameter wildcard. The next moves are going to be wild.

Official launch website

Microsoft

Microsoft made Quake II playable with AI

So Microsoft decided to let its AI make a game level. Not just any game Quake II. If you're thinking “Whoa, that’s cool,” you’re not wrong. But also… it’s weird.

They dropped a browser-based demo using their Copilot AI platform. You can play it.

Here’s what actually happened:

• Microsoft trained its Muse AI models on a Quake II level it owns (thanks to buying ZeniMax).

• The result: you can move, jump, crouch, and blow up barrels like you’re in the real game.

• But enemies? Blurry. Health bars? Off. And if something leaves your screen for more than 0.9 seconds… the AI forgets it exists.

• Yup, it has object permanence issues. Look down at the floor, look back up you might teleport or spawn enemies out of nowhere.

• Microsoft admits it’s not really a game it’s a model simulating a game. Big difference.

• It’s a fun experiment, but not a playable replacement for the real thing.

• Critics like Austin Walker called it out, saying this tech misunderstands how actual game systems work the code, art, and surprises that make real games feel alive.

Here’s what I think:

This is fascinating tech… but not a time machine. If AI wants to “preserve” games, it has to do more than mimic visuals and movement. Games aren’t just what we see they’re what happens when we push them too far.

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