>His name is Abhinav.
>He went on a trip to Bali and a beautiful German girl named Safira instantly fell for his natural charm.
>He didn't have to fund expensive cafe dates or deal with any unnecessary attitude.
>She didn't ask for his bank balance or salary package; she just loved him and invited him straight to Germany.
>Now he is living his best life in a gorgeous wooden house hand-built by her father.
>He is exploring underground natural fridges and enjoying the ultimate European village vibe.
>Indian girls with a 10-page list of unrealistic demands are watching his vlogs and fuming in jealousy.
>He completely bypassed all the dating drama and secured a massive international win for the boys.
Why tolerate the delusional standards of modern Indian girls when an international flight ticket is literally cheaper?
For all the young founders who told me two or three years ago that they had to drop out of school to start companies at that moment or it would be too late:
I love @satyanadella his ability to put technology transformations in simple terms is par none. In this instance I think it's important to understand the distinction in consumer, horizontal multi-tenant AIaaS and Enterprise which tends to be deep and vertical.
1. Consumer - this is not new news, the consumer has always been part of the product. Be it search (Bing or Google), social media (think TikTok, Snap, and of course FB), even unassuming products like Maps have always retained the knowledge learnt from customers, customers suspecting or unsuspecting have always had the choice. Use the product and share your prompts, location or preferences and that will be used to build a better product. So why is that surprising if it happens in AI, the model complex will continue to use consumer usage to train fundamental multiple modalities. This is the biggest technological event of our lifetime :).
2. Horizontal AIaaS (AI capability that doesn't need to be too enterprise specific - can be tuned, but is a 80% common use case) - Think coding, legal, many current SaaS categories - most likely agentic development for prosumers. All of this behavior is being used to train the model complex to get better at all these. The large swath of small medium size businesses will be fertile training grounds for such applications. They cannot deal with isolated apps and custom deployments.
3. Enterprise deployments - this is where I am not sure the reverse information paradox applies. There is an existing model of isolated single tenant public cloud deployments, deployments where our data, code and connectivity are both isolated and in the hands of the enterprise. This is the deployment we have for our development from all frontier models. All our grounding data, prompts, internal tribal knowledge is sequestered. This is important because this is where enterprise IP will reside. It will be a large task to capture, collate, interpret this data. Equally complex to maintain, evolve and make effective an enterprise AI architecture. But that is what we all will need to sign up for.
This is not a cloud vs on prem debate, they can both be equally secured. On prem is probably more unwieldy at the moment given the fast pace of development.
Un ingénieur IA senior chez Microsoft vient de dévoiler comment les équipes de Microsoft créent des agents IA avec Anthropic.
34 minutes de workshop gratuit, directement par l’équipe Microsoft.
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Opus 4.7 + plus de 1 400 outils MCP déjà prêts à l’emploi.
Tu connectes Claude à un agent → tu lui ajoutes des outils → tu déploies en production.
Plus utile que la majorité des formations de vibe-coding vendues 500 $.