Google Just Reset the AI Race

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If you blinked this month, you probably missed three AI plot twists and a small tech cold war.

Some tools got wildly faster. 

Others got wildly cheaper. 

One might be in trouble with the Pentagon.

Meanwhile, your workflow quietly changed.

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🎭 Goodbye Uncanny Valley? Meet Phoenix-4, a real-time AI human rendering model that generates every pixel of a face from scratch — at 40 FPS in HD — while shifting naturally between 10+ emotional states mid-conversation. Trained on thousands of hours of real human dialogue, it reacts contextually, aiming to make AI avatars feel less robotic and more genuinely “present.” Tavus sees big potential in healthcare, education, and sales — anywhere feeling heard can change outcomes. But as AI faces get more convincing, so do the risks of digital deception.

👓 Siri Is Getting Eyes (and Ears). Apple is reportedly fast-tracking three camera-powered AI wearables — a pair of smart glasses, a pendant dubbed the iPhone’s “eyes and ears,” and camera-equipped AirPods — all designed to give Siri real-time visual awareness. The glasses (targeted for 2027) and other devices would feed live context to a revamped Siri, expected to debut with a chatbot-style interface in iOS 27 powered by Google’s Gemini. If Apple pulls it off, it could instantly reshape the AI hardware race.

🧪 AI Just Did The Math. OpenAI says GPT-5.2 has made what it calls AI’s first original contribution to theoretical physics — identifying an error in a supposedly solved particle physics problem and independently producing a corrected formula with a formal proof in just 12 hours. The work was verified by physicists from Harvard, Cambridge, and Princeton, with one noting the AI took a path “no human would have tried.” If confirmed, it signals a shift from AI assisting research to actively challenging long-held scientific conclusions. The debate over whether AI can generate truly “new” ideas just got a lot more serious.

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The third week of February 2026 was less “AI update” and more “AI reshuffle.” 

Google dropped benchmark scores so high they look typo-level, OpenAI went full speed demon with a 1,000+ tokens/sec coding model while tightening security screws, Anthropic squeezed flagship power into a budget tier while sparring with the Pentagon, and Google quietly made AI music creation mainstream. 

Models are getting faster, cheaper, more autonomous, and more politically entangled. 

Key Points You Shouldn’t Miss

Deep Think’s 84.6% on ARC-AGI-2 isn’t a small lead — it’s a 16-point gap over Anthropic and a 30+ point gap over OpenAI. 

That’s separation. 

Add a 3,455 Codeforces Elo (elite competitive-programming territory) and Olympiad-level science scores, and you’re looking at a reasoning engine designed for frontier math and physics, not just chatbot polish.

But the sleeper move is pairing that with Lyria 3 inside Gemini. On one end, Google is pushing high-level autonomous math agents like Aletheia that verify proofs. On the other, it’s letting everyday users generate 30-second songs with auto lyrics and cover art — all watermarked via SynthID. 

That’s a full-stack play: frontier intelligence + consumer reach.

Codex-Spark pumping out 1,000+ tokens per second changes behavior. 

When feedback is instant, iteration skyrockets. 

Yes, Spark trails the full 5.3-Codex on benchmarks like SWE-Bench Pro — but finishing in a fraction of the time is often more valuable than squeezing out a few extra percentage points.  

Then there’s the hardware shift. 

Moving beyond Nvidia into Cerebras (plus AMD and Broadcom deals) isn’t just supply diversification — it’s strategic leverage. 

AI companies that control their compute destiny control their margins.

And Lockdown Mode? That’s realism. 

As models evolve into agents that browse, execute, and connect to apps, “hard off switches” may be more reliable than soft warnings. Deterministic limits beat probabilistic hope.

Sonnet 4.6 hitting 79.6% on SWE-Bench Verified at 1/5 the cost is brutal for competitors. 

That’s near-flagship capability at volume pricing. With a 1M token context window and OSWorld scores jumping from <15% to 72.5% in about a year, agentic computer use is no longer experimental — it’s accelerating fast.

But the Pentagon standoff reveals a deeper layer of the AI race: governance. 

If labeled a “supply chain risk,” Anthropic could lose major defense contracts. 

The core disagreement? Whether AI should be usable for “all lawful purposes,” including military applications Anthropic wants to restrict.

AI just became faster, cheaper, and more embedded into the tools people already use — which means your workflows are about to change whether you plan for it or not. 

Speed-optimized models shrink feedback loops, lower-cost near-flagship systems shift budget math, and advanced reasoning agents can now pressure-test ideas in minutes instead of days. 

At the same time, tighter security controls signal that guardrails will soon be a standard part of serious AI use. 

AI is spreading into infrastructure, creativity, defense, and cost strategy all at once.

So don’t ask, “Which AI is best?” Ask, “Which AI fits this task right now?” 

Speed, cost, reasoning depth, distribution, and policy stability are now separate levers. 

The smartest move in 2026 isn’t loyalty — it’s flexibility.

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A playground for your imagination (and low-key prompt skills).

Each send, we give you a customizable DALL·E prompt inspired by a real-world use case — something that could help you in your business or job if you wanted to use it that way. But it’s also just a fun creative experiment.

You tweak it, run it, and send us your favorite. We pick one winner to feature in the next issue.

Bonus: you’re secretly getting better at prompt design. 🤫

Last week, we challenged you to test GPT-4o’s visual generation skills with this prompt.

Here’s the WINNER:

Congrats to Marlon for his creation!🥳

Want to be featured next? Keep those generations coming!

Inside a fast-moving train at sunrise, warm golden light floods through a large panoramic window, casting long streaks of orange and soft pink across a minimalist fold-out table. Outside, the landscape blurs into motion — fields, distant cities, early-morning haze — but inside everything feels still and intentional. Resting on the table is [your object], rendered in ultra-detailed, photorealistic clarity. Its materials catch the sunlight beautifully — glass glowing softly, metal edges reflecting warmth, subtle textures crisp and precise. The camera frames the scene from an intimate side angle, shallow depth of field, cinematic color grading, high-end product realism — capturing the quiet feeling of building something while the world moves forward.

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