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Gen Z is rotating into ETFs. Unleveraged ETFs rose to 21.9% of Gen Z equity net flow (June→July), and ETF trading share climbed to 25% in early August (vs 9.5% for Millennials). More baskets, fewer single names—diversification over speculation. Read more 👉

Grok Build mode is so much fun! I made a few quick games for my nephew in just minutes using simple one-line prompts, all from the Grok iOS app on my iPhone. This is honestly one of the coolest things ever!

After using Grok Bot nonstop for the past week I'm going to say it: it's the best AI agent out there right now Dead simple and just works It eliminates the 10,000 decisions, configs, and fixes that scare people off The integrated cloud computer unlock so many use cases too: 1. Invited the cloud computer to my community. It opened it up and now monitors the community 24/7. Answering questions and DMs 2. Uses the X plugin to monitor all the AI companies X accounts every 15 minutes around the clock. Looking for updates and big news, alerting me the moment it happens 3. Clicks around testing the 2 apps I'm building around the clock. Looking for bugs, thinking of new features, then writing the PRs and waiting for my review 4. My Grok Bot checks my social media channels around the clock. Moment I post anything, it repurposes the content based on other content I've posted, making writing my newsletter much easier 5. The integrated Grok images are really nice. So I can tell it to go to my YT on its cloud computer and make similar thumbnails for my new videos 6. Checks data in post hog on my product retention, gives me a list of at risk subscribers, prepares emails and reachout, then asks me for the OK Can the other AI agents out there do this? Yes. There's literally nothing Grok Bot can do that the others can't. But here's the thing, the user experience is designed so beautifully that it unhobbles all of these use cases and make them so much more pleasant to execute on Grok Bot is a must try

A reported $12.5B Lakers valuation prices more than games and trophies - it prices history, media rights, global attention, and fan identity. The next owner still has to make that financial value feel like it belongs to the community. #Lakers# #NBA# #SportsBusiness# #PodcastorAI#

OK let’s try this: ———————- Pretend you’re 5 and the algorithm is a smart robot that picks which toys (posts) to show you in your toy box (For You feed). The robot doesn’t just count how many times people already played with a toy (likes, reports, etc.). Instead, it looks at you and guesses: • “How likely is this kid to like this toy?” • “How likely is this kid to report this toy as yucky?” • “How long might this kid play with it?” Those guesses are little numbers between 0 and 1 (probabilities). The “weights” are like special multipliers the robot puts on those guesses: • A like-guess might get multiplied by a small number (like 0.5). • A report-guess might get multiplied by a big negative number (like –234). Then the robot adds all those multiplied guesses together to give the toy a final “yay or nay” score and sorts the toys by that score. Why the numbers look so big and why people get confused Reports almost never happen, so the robot’s “will you report this?” guess is usually a tiny number (like 0.0001). To make that tiny guess still matter a little bit in the final score, they give it a big multiplier. People sometimes look at the big number and think “1 report = 468 likes!” 
That’s wrong. It’s not counting real reports or real likes. It’s only multiplying the guesses the robot made about you. If the robot thinks you’re the kind of person who almost never reports anything, even a big weight on “report” barely moves the score. The whole thing is personalized to how you usually behave. The people who wrote the code even put big comments in the GitHub repo so no one (and no other robots) gets confused about this again. That’s the whole idea in kid words: the weights turn the robot’s personal guesses about you into a ranking, not a simple “count the hearts and flags.”