🚨 Google’s pressure triggers OpenAI code red

Google is closing the gap in AI, and OpenAI knows it. After spending time on side projects, the company is now shifting its attention back to ChatGPT to stay ahead and strengthen its core product. Let’s dive in!

In today’s insights:

LATEST DEVELOPMENTS

Evolving AI: OpenAI hits pause on side projects to boost ChatGPT.

OpenAI is shifting attention back to ChatGPT after internal signals that Google and Anthropic are catching up. Sam Altman told staff to focus on speed, reliability and better answers. Daily calls and temporary team transfers are part of the push. Google’s momentum, boosted by tools like its Nano Banana image model and strong Gemini 3 scores, is raising internal urgency.

Looks like we’re entering a phase where AI tools you rely on, like ChatGPT or Gemini 3, aren’t just competing on hype but on how well they work day to day. This pressure among big players could mean more accurate, snappier tools landing sooner. A sharper focus on ChatGPT means users could soon see faster replies, fewer hiccups and more relevant output. The bigger question is how long OpenAI can hold its lead now that its rivals are moving fast too.

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Evolving AI: Mistral rolls out a new multilingual and multimodal model family.

Mistral released a full suite of open models, with Large 3 trained on roughly 3,000 H200 GPUs and listing 41B active parameters. The smaller Ministers focus on local setups and offer solid instruction and reasoning results, with the 14B model reaching strong scores. Everything is available through major cloud platforms and Mistral AI Studio.

Read Mistral’s announcement here →

Mistral 3 is very practical: a strong open model you can self host, plus smaller multimodal variants that fit laptops, edge servers and tight latency budgets. That mix cuts cloud spend, helps with data residency, and makes it easier to ship AI features into SaaS, on-prem tools, and even hardware without waiting for a big vendor to support your use case. In a year where DeepSeek, Qwen and others keep pushing open models closer to top proprietary systems, Mistral adds a European option that companies can fork, audit and plug directly into products today.

Evolving AI: Colleges start using AI to read student essays.

AI is showing up in admissions offices as colleges test tools that review essays, scan transcripts and check research submissions. Virginia Tech now uses an AI reader to score short essays, speeding decisions by weeks. Caltech uses a chatbot interview to confirm whether applicants truly understand the research they submit. The shift is new, uneven and already sparking debate.

AI is slipping into a part of life that feels deeply personal: who gets a shot at college. For admissions offices drowning in applications, tools that can scan 250,000 essays an hour and double check scores sound like relief, and they help schools hit decision dates instead of dragging into spring. But for students, it means essays are now written under one set of AI rules, then judged with another, often invisible one. Fairness, bias and transparency stop being abstract ethics-panel topics and turn into very practical questions: who trained this model, what does it reward, and would you feel comfortable if it was ranking your kid’s story?

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QUICK HITS

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🤖 Leaked "Soul Doc" reveals how Anthropic programs Claude’s character.

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