Wall Street spent years demanding AI investment, then panicked when AI investment showed up on the balance sheet: If Alphabet keeps printing record profits while building the infrastructure for the next decade, this may end up looking more like impatience than prudence. The market loves growth, until it has to pay for it.

It’s even worse! SpaceX includes XAi and XTwitter: cash burning nonsense. The only good thing about SpaceX is Starlink.

I’m a huge fan of the Fediverse, but the barriers are so incredibly high that it’s unlikely a large number of people - let alone a majority - will find their way here.

Isn’t he just talking to bots there anyway, who can’t buy shares?

Perfect shouldn’t become the enemy of better. Open Weight AI isn’t Open Source AI, but it’s a huge improvement over Closed AI where you get neither the weights nor the training pipeline.

The irony is that platforms spent years making anonymity optional, then built engagement systems that rewarded the worst actors anyway. Now the proposed fix is more identity, more biometric data and more addictive UX.

Ultimately, everyone, because associations, clubs and small towns are mainly or exclusively active on Facebook: anyone who wants to take part will still have to use Facebook. 🤷

They didn’t short rockets: They shorted Elon Musk’s promise machine. For years he’s sold investors a never ending stream of revolutionary breakthroughs that were always just around the corner. Eventually reality catches up. Even the world’s best engineers can’t justify a valuation built on perpetual hype instead of consistently delivered results.

Wall Street spent years pricing Tesla like a future AI empire instead of a car company. Now investors are getting a reminder that robotaxis, humanoids and promises don’t magically pay today’s bills. Reality has an annoying habit of showing up right after earnings season.

More and fresh is better.

Zuck seems to be trying to boost his data for the facial recognition feature on Meta glasses. 🙈

OpenAI is a good reminder that mission statements and business incentives don’t always stay aligned. That said, I’d judge DeepSeek less by the rhetoric and more by what they actually release. Hype is cheap: open weights, reproducible results and useful tools are much harder to fake.

This. The frontier race is about building the smartest generalist, but most companies don’t need that. They need a specialist tuned to their workflows. Narrower scope means smaller models, lower costs, faster inference and often better results. General models become the foundation, not the finished product. It’s still all to play for! 💪😎✌️

That’s either incredibly idealistic or a very smart strategy: Open models grow ecosystems faster than walled gardens, but compute still decides who gets to play at the highest level. If AGI really becomes shared infrastructure, the moat shifts from models to chips, data and execution.

It was just as you’d expect: This isn’t an AI problem! It’s the same human problem we’ve always had: misconfigurations, weak security, and avoidable mistakes. AI just punishes those errors faster and more effectively than traditional software ever could. Anyone who continues to rest will be severely punished.