Mistral’s new model makes "reasoning" its superpower

Hey there,

Hope you’re having a good weekend.

Here’s what you might’ve missed and make sure to read to the end for the giveaway and amazing tools.

In today’s post:

• Mistral reasoning model “Magistral“ is something else

• The world after DeepFakes

• Google broke the deal with Scale AI

• Running Llama model on Pentium II computer

• Trending AI tools + Midjourney prompts giveaway

What’s Trending Today

Breakthrough

Magistral isn't just smarter it thinks more like us.

Mistral AI just released Magistral, a new model focused on advanced reasoning.
It’s a big move not toward scale, but toward making AI more explainable and useful in the real world.

Here's everything you need to know:

• Magistral comes in two versions: an open-source Small and an enterprise-grade Medium.

• Unlike previous models, it uses a step-by-step reasoning chain that users can follow and audit.

• Small runs locally on affordable hardware, giving developers privacy and control.

• Medium is faster and available via Mistral’s API with deployment across major cloud providers coming soon.

• Performance tests show it outpaces previous Mistral models and rivals DeepSeek on key benchmarks.

• Mistral is aiming for high-stakes tasks: legal research, financial forecasting, and regulatory work.

• But it’s also open to creative uses like writing and narrative generation.

Here’s what I think:

Magistral marks a shift in AI from just powerful to thoughtfully designed.
We’ve spent years chasing scale. This model asks a better question: can we build intelligence that reasons like people do?

It’s a bet on clarity over complexity and it’s one to watch.

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What goes wrong in AI

From memes to deepfakes the spaghetti test is over.

AI video once meant glitchy horror. Now it means Will Smith eating pasta convincingly, and with sound.

Here’s everything you need to know:

• In 2023, a fake Will Smith eating spaghetti became a viral disaster — and an unexpected benchmark.

• This year, Google’s Veo 3 recreated that moment with smooth visuals, synced audio, and one strange quirk: crunchy noodles.

• That odd sound aside, Veo 3 marks a stunning leap in AI realism not gradual progress, but a cliff jump.

• Hollywood is taking notice. Studios like Amazon now openly use AI tools to cut costs and streamline production.

• The real shift? Anyone can now create near-perfect fake videos for under $2 no studio required.

• Deepfake threats are scaling fast, with public figures like Tom Hanks already fending off AI misuse.

• Even with flaws and guardrails, these models are evolving too fast for current trust systems to keep up.

Here’s what I think:

The spaghetti video wasn’t just a meme it was a warning. Now that AI can mimic reality this well, the question isn’t just “Is this real?” It’s “Can I trust who’s showing it to me?” We’re entering an era where truth depends less on what we see, and more on who we believe.

Deals

Google Just Broke Up With Scale AI

Scale AI was Google’s biggest data-labeling partner. But now that Meta owns nearly half of it, the relationship is over.

Here’s everything you need to know:

• Google is planning to pull its $200M business from Scale AI after Meta took a 49% stake.

• The move reflects fears that Meta could gain visibility into rivals’ research, roadmaps, and prototype data.

• Other giants like Microsoft, OpenAI, and xAI are also scaling back or cutting ties.

• Scale AI risks losing its core customers the very labs building next-gen AI models.

• Competitors like Labelbox, Handshake, and Mercor are seizing the moment, reporting surges in demand.

• Some labs are shifting to in-house teams, prioritizing data security over outsourcing.

• The fallout marks a turning point: neutrality in AI infrastructure is no longer optional.

Here’s what I think:

The Meta-Scale deal exposed a hidden truth in AI, trust is infrastructure.
When one company touches your data, your strategy, and your models, even a partial ownership stake becomes a risk. This is more than a vendor shakeup it’s a reset in how the AI world handles trust and power.

Tech

This AI Runs on a 1997 PC. Seriously

A bold team just ran a compressed Llama model on a 1997 Pentium II. The result isn’t just a tech stunt it’s a glimpse at a radically different future for AI.

• The setup: a dusty PC from 1997 with 128 MB of memory and Windows 98.

• They used BitNet, a model architecture designed for ultra-compact AI deployments.

• Old tools like Borland C++ and FTP became workarounds for modern bottlenecks.

• Despite extreme limits, the model ran locally no GPU, no cloud, no tricks.

• This shows that powerful AI doesn’t have to rely on centralized, expensive infrastructure.

• For low-resource regions or privacy-focused use cases, this could be game-changing.

• The team plans to open-source their methods, hinting at broader applications beyond just nostalgia.

Here’s what I think:

This isn’t about retro computing. It’s about what happens when we stop assuming AI needs massive resources. When models shrink and systems get smarter, even 90s hardware can become relevant again.

In a world chasing scale, this project whispers a different promise: access for all.

AI TOOLS + Giveaway

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