For 40 years, software waited for you to click. That contract just ended. What comes next isn't a better app -- it's a different relationship with your entire stack.

Everyone talks about what AI replaces. Nobody talks about the validation layer it created -- and why you need more senior people, not fewer.

You paste client briefs, contracts, and pricing strategies into a cloud AI. The model isn't bound to silence. Your clients don't know you made that decision for them.

Most companies assess their security posture once or twice a year. Private AI changes that equation completely.

The next AI failure won't be a model that can't think. It will be a model that thinks clearly about the wrong things.

Anthropic just ran the largest qualitative AI study ever. 81,000 people. The findings aren't the story. The method is.

The interface we've used for 40 years is disappearing. And most software is still designed for a world that no longer exists.

Most technology leaders get it backwards. They optimize for risk, for control, for internal excellence. But none of those close deals.

Everyone is telling service firms to become AI companies. That advice will destroy more mid-size firms than AI itself.

Everyone's telling service companies to become AI companies. That's the wrong advice. The winning move is making AI work inside the messy reality you already know.

McKinsey's AI platform was reportedly breached in two hours. If they can't secure it, what does that mean for Canadian SMBs using the same tools?

Karpathy's AutoResearch runs 100+ ML experiments overnight on a single GPU. The researcher's job just changed.

Most AI advice to small businesses skips the real question: where does your data live while the AI is doing your work? For Canadian SMBs, the answer shapes trust, compliance, and resilience.

International Women's Day. Not a celebration post. A recognition of competence so undeniable that the noise becomes irrelevant.

AI doesn't replace your people. It makes all of them builders. What Anthropic learned internally is what every SMB needs to hear.

Cloud AI is convenient until it isn't. For small businesses, owning your AI infrastructure is about control, cost, and common sense.

A walkthrough of the box that brings AI to businesses that will never hire a developer.

They need something that just works.

What happens when AI removes the consumer from the economic loop?

The hardest translation isn't tech to business. It's vision to trust.

Why this site exists, and what it's for.

Pas comme une devise. Comme un contrat de société.

The gap between success and failure isn't talent. It's what you do when no one's watching.

Optimism about AI seems less about the technology itself and more about whether people believe the future still has a place for them.

Technology is not the strategy. It is only a lever.

Energy is quickly becoming the main constraint in scaling computing resources globally.

You cannot teach people unless they want to learn — and when they want to learn, there is nothing to stop their progress.

The urge to incorporate AI into enterprise flow is big. I see the pressure and FOMO everywhere.

Refuser l'IA, c'est refuser d'écrire le prochain chapitre de notre propre histoire.

Une société qui veut tout prévenir finit par tout interdire.

L'aventure ne fait que commencer.

I'd trade a thousand terabytes of knowledge just to feel what it's like to hold a cup of coffee.

Le risque n'est pas l'IA. Le risque est de continuer à piloter nos organisations comme des usines à tâches.

Un bon cadrage aujourd'hui évite les regrets demain.

Si vous cherchez un vrai contact, le regard de vrais humains, vous ne le trouverez plus de l'autre côté de vos écrans.

Croître n'est pas toujours grandir. La vraie croissance est exigeante. Elle coûte moins mais vaut plus.

Une stratégie brillante échoue si son exécution est bancale.

Ne baissez jamais la garde quand vous êtes en ligne.

From the creator of the technology to a troubled alarmist of its consequences — Hinton is following the path of Oppenheimer.

Those who control these foundation models are the superpowers of tomorrow.

What really is reasoning? And do we even have a good understanding of reasoning in humans?

Real transformation doesn't always come from the top down — it often starts with people on the ground.

What are the long-lasting, never-depreciating skills a knowledge worker needs for a lifetime-resilient career?

Fixed tokenizers are a source of bias in our models. What if we went back to bytes?

We are still at the early times of enterprise AI. Here are the real hurdles companies face.

AI development is concentrated in just a few regions. That concentration risks bigger economic gaps, biased systems, and missed local solutions.

Les optimistes voient un potentiel énorme. Les sceptiques voient la dépendance. La vérité est entre les deux.

There is less need to advertise. There is an absolute necessity to appear in organic results to target AI agents.