In partnership with

74% of Companies Are Scaling AI with Real-Time Web Access

Scaling AI shouldn’t be slowed down by blocks, downtime, or slow processes. Manual fixes and unreliable public web data put a cap on what your automations and AI agents can achieve.

Bright Data provides seamless, real-time access to public web data even from challenging sites, guaranteeing a continuous pipeline for your models and agents. Your automations run, your AI trains on live data, and your teams stay focused on innovation and growth, not troubleshooting.

Companies using Bright Data are already scaling their products and achieving real ROI with public web access at scale. Move at speed and scale with Bright Data.

Alphabet's Race to $4 Trillion: Why Google Just Became Nvidia's Nightmare

Listen, something remarkable is happening with Alphabet right now, and it's not just another tech stock having a good year.

We're talking about a company sitting at $3.93 trillion in market cap—up 82% in twelve months—and literally weeks away from crossing the $4 trillion threshold. But here's the kicker: this isn't hype. The fundamentals actually support it.

The Gemini 3 Moment

Google's new Gemini 3 model just did something that caught even the skeptics off guard. On the hardest AI reasoning tests, it's not just beating OpenAI's GPT-5.1—it's demolishing it. We're talking 91.9% versus 88.1% on scientific reasoning, and a 45.1% score on abstract visual problem-solving where GPT-5.1 managed just 17.6%.

But the real story is agentic reliability. When they tested these models running a simulated business for an entire year, Gemini 3 generated 272% higher returns than GPT-5.1. That's not a rounding error. That's the difference between an AI that actually works and one that just sounds impressive.

The Financial Reality

Alphabet just posted its first $100 billion revenue quarter. Google Cloud jumped 33.5% year-over-year, now pulling in over $15 billion quarterly with backlog contracts worth $155 billion. The company signed more billion-dollar deals in nine months than it did in the previous two years combined.

The TPU Wildcard

Here's where it gets interesting. Meta is reportedly negotiating to deploy billions of dollars worth of Google's custom AI chips—TPUs—starting in 2027. Why does this matter? Because Nvidia currently owns 95% of the AI chip market, and if Google captures even 10% of Nvidia's $51 billion quarterly data center revenue, we're looking at a $5-10 billion annual business materializing out of nowhere.

The thing is, Nvidia's Blackwell chips are backordered into 2026. Google's chips use 40% less power and deliver 50x less downtime at scale. When supply constraints meet viable alternatives, monopolies crack.

What Happens Next

Warren Buffett—yes, that Warren Buffett who famously avoids tech stocks—just dropped $5.18 billion into Alphabet. That's twice his Amazon position. When the world's most conservative investor bets big on your AI infrastructure play, the market pays attention.

The path to $4 trillion isn't a question of if anymore. It's a question of when—and whether Google can actually monetize the $91-93 billion they're spending on infrastructure this year alone.

The AI hierarchy is reshuffling in real time.

Reply

or to participate

Recommended for you

No posts found