The Thinking Game takes you on a journey into the heart of DeepMind, capturing a team striving to unravel the mysteries of intelligence and life itself. Filmed over five years by the award winning team behind AlphaGo, the documentary examines how Demis Hassabis’s extraordinary beginnings shaped his lifelong pursuit of artificial general intelligence. It chronicles the rigorous process of scientific discovery, documenting how the team moved from mastering complex strategy games to the ups and downs of solving a 50-year-old "protein folding problem" with AlphaFold. Following its world premiere at the Tribeca Festival and a successful international tour, the film is now available here for all to watch for free. https://youtu.be/d95J8yzvjbQ?si=dcwL3cPkZA5SQaC1

Until now, every data system has been reactive. Something breaks → you fix it. A metric drops → you investigate. But with AI loops, data is starting to correct itself. Imagine systems that: - Detect anomalies before humans notice. - Rewrite broken tags automatically. - Adjust predictions as new context streams in. This is the next leap — autonomous data refinement. In this world, data doesn’t just describe reality — it maintains it. The job of tomorrow’s analyst isn’t cleaning spreadsheets. It's designing feedback loops that keep truth stable at scale. Data Alchemy has always been about transformation. Now it’s about continuous transformation — in real time.

Everyone’s chasing bigger models and cleaner data. But the real leap in AI performance now comes from one thing: context. The same model with better context outperforms a “smarter” model every time. Context is what turns data into understanding — - who the user is, - what environment they’re in, - why the signal matters right now. Without context, even perfect data gives wrong answers. With it, average models become brilliant. That’s why the next frontier isn’t just model training —it’s context engineering. The future of AI isn’t more parameters. It’s richer meaning per parameter. Data alchemists who master context will define how intelligence actually feels.

Hey Champs ! Well, I was alking to one of my old friend and he is en excellent guy in data architecture and looking for someone who can do a live project with him for co-learning. If any is interested let me know I will just help both of you to connect. Purpose: 1. Need to learn complete AI model development lifecycle 2. Develop a project working on a real life use case. 3. Learn and share knowledge on dfferent aspects of AI.

At this time I am creating an external software for notion, which can connect to the notion databases and allow to track the time and use some techniques such as Pomodoro and Flowmodoro My goal with this project is to solve 3 problems that notion currently has when trying to register time: 1 - Notion is not automatically updated, so you cannot see how time progresses in a minute to minute native timer 2 - Notion does not allow to place a sound that indicates when the time is over without using automations. 3 - You cannot place clear visual elements that indicate that time is running, so sometimes you could forget to stop the timer Let me know your opinion about this, do you think would be a useful product ? ⬇️