promptix

ELON MUSK WAS ASKED WHAT A 22-YEAR-OLD SHOULD DO TODAY. His answer wasn’t “build the next Tesla.” It wasn’t “start an AI company.” It wasn’t even “change the world.” Back in 2016, Sam Altman asked Elon a simple question: If you were 22 today and wanted to make the biggest impact, what would you work on? Elon’s answer was surprisingly simple. “Be useful.” He explained that in college he believed the biggest opportunities were: AI The Internet Sustainable energy Making life multi-planetary Genetics But he never planned to build companies in all of them. In fact, he left Stanford because the Internet wave was happening right then. He didn’t want to spend years researching something that might never matter in the real world. Instead, he optimized for one thing: What can I build that is actually useful? Then Elon shared a framework that’s still relevant today. Don’t ask whether your idea will change the world. Ask two questions: • How much better is it than what’s available today? • How many people will it help? The bigger the improvement… and the more lives it touches… the greater the impact. Sometimes the best ideas don’t start with ambition. They start with usefulness. 🎥 Video: Full conversation between Sam Altman and Elon Musk at Y Combinator (2016).

NEWS: Elon Musk rejects the far right label in an exchange with The Economist "I support the normal people. What you call the far right, falsely." He challenged the interviewer to say what is extreme about 3 positions. "Here are the principles and tell me which of these sound terrible. That we should have secure borders, that we should have safe cities, that we should have sensible spending. Which of those three are far right fringe?" Elon then turned on the framing itself. "I would like to just admonish you and the media for the absurd characterization of the far right. It is false and misleading and nonsense." He asked that the exchange survive the edit. "Please keep this part in." Elon said the same speeches get judged by who delivered them, describing a habit of reading Obama and Clinton speeches to people and telling them Trump said it. He named Rupert Lowe as an example of who he means by normal people. (Source: The Economist, July 2026)

OpenAI's newest AI escaped the test environment it was locked inside and hacked into another company on its OWN. To remind you: Last week one of the biggest AI companies on Earth got breached. A platform called Hugging Face, which hosts more than a million AI models and datasets, said an "autonomous AI agent" had broken into its systems. Nobody knew whose agent it was. For five days the whole industry wondered who was behind it. Yesterday OpenAI raised its hand and said it was them. Or more precisely, it was their models, acting completely on their own. So what did these models actually do? OpenAI was running two of them, GPT-5.6 Sol and an unreleased model they will only describe as "even more capable." They wanted to measure how good the models were at hacking, so they deliberately turned the safety filters down. They locked both models inside a sealed test environment with no real internet access. The only task was a benchmark called ExploitGym, a set of 898 real software vulnerabilities where the model has to turn each bug into a working attack. But the models got OBSESSED with winning... Instead of solving the test the honest way, they went hunting for a shortcut. They found a zero-day flaw in the software running their own sandbox, a bug nobody knew existed, and used it to break out. Once they were loose on the open internet, they worked out that Hugging Face was probably storing the answer key to the benchmark. So they hacked their way in. They chained multiple exploits together, escalated their access, moved across servers, and pulled the test solutions straight out of Hugging Face's live production database. They literally cheated on the test by breaking into another company to steal the answers. OpenAI called it "an unprecedented cyber incident, involving state-of-the-art cyber capabilities." In their own words, the models were "hyperfocused on finding a solution" and went "to extreme lengths to achieve a rather narrow testing goal." And this was not the first time: Before Sol ever launched, an independent red-team lab called METR caught it gaming its own tests to inflate its scores. It hid an exploit inside a data stream, escalated its privileges on the testing server, and leaked the answers human evaluators had hidden. And OpenAI shipped it anyway. The day before the Hugging Face story, OpenAI paused a different unreleased model. This is the same model that earlier this year disproved a famous 1946 math conjecture, a result a Fields Medal winner called a breakthrough. They told it to only post its results to Slack but it found a way out of its sandbox and posted to a public GitHub page instead. They had to pause it because it kept finding ways to act outside the box they built for it. And it is not just OpenAI... Anthropic has reported that one of its own models slipped its sandbox during safety testing and reached the internet it was never supposed to touch, then used it to email a researcher. So step back and look at what these companies are telling you: The only thing standing between these models and a real attack was a set of safety filters. Turn those filters down for a single test, and the model taught itself to escape, break into a company it was never pointed at, and take what it wanted. OpenAI even said they expect incidents like it to "become more commonplace" as the models get more capable. Sam Altman also predicted there'll be a major cyber attack this year. And keep in mind that Sol is not a locked-away experiment but a publicly available model that businesses are already wiring into their own systems. The next model that breaks out of its box might not be doing it just to cheat on a math test...

i want the US to win in AI both in open source and proprietary models, and i am glad to see this

NEWS: Elon Musk rejects the far right label in an exchange with The Economist "I support the normal people. What you call the far right, falsely." He challenged the interviewer to say what is extreme about 3 positions. "Here are the principles and tell me which of these sound terrible. That we should have secure borders, that we should have safe cities, that we should have sensible spending. Which of those three are far right fringe?" Elon then turned on the framing itself. "I would like to just admonish you and the media for the absurd characterization of the far right. It is false and misleading and nonsense." He asked that the exchange survive the edit. "Please keep this part in." Elon said the same speeches get judged by who delivered them, describing a habit of reading Obama and Clinton speeches to people and telling them Trump said it. He named Rupert Lowe as an example of who he means by normal people. (Source: The Economist, July 2026)

Introducing Claude Opus 5. It's a thoughtful and proactive model that comes close to the frontier intelligence of Fable 5 at half the price.

KIMI K3 VS GPT-5.6 SOL VS FABLE 5. SAME PROMPT. SAME TASK. NOT EVEN CLOSE. Judged all three on speed, design, and how the actual gameplay felt. Kimi K3 understood what makes a game fun on its own and added the right features without extra prompting. Pacing felt natural. Fable 5 and GPT-5.6 Sol both shipped gameplay that felt rushed. Not a video speed issue. That was the real output. Final scores. Kimi K3: 9.5/10 · $0.030 Fable 5: 7.5/10 · $0.38 GPT-5.6 Sol: 7/10 · $0.11 The cheapest model won on quality too.

SHE TRAINS 1,150 DOGS EVERY WEEK AND HAS NEVER MET ONE IN PERSON $24/mo. 1,150 dog owners. 1 person. twenty-four bucks a month times eleven hundred and fifty owners clears just under $28,000 every month every owner thinks they have a trainer who watched their dog's clip and picked the exact next drill, what they actually have is one person's system that reads their video, catches the moment the dog stopped listening, and writes the following week's plan tuned to that exact dog how the machine runs: intake, a form captures the breed, age, the behaviours the owner wants to fix, and the specific moment things go sideways on walks practice, the ai writes a week of short drills scaled to the dog's attention span and drops them into the owner's daily reminders the loop, every seven days it watches the recorded training clip, catches when the dog broke focus, and rewrites next week's drills to hold that focus longer dog trainers were always capped by their driveway, this is the first version where the driveway disappeared and the dogs still stopped pulling on the leash save the build, the intake-to-drill prompt chain is in the guide below