Currently, you hear this from many quarters; Fortune recently published an article stating that it's being whispered that the next six months will change everything. I can only speculate, but it currently looks like exponential growth is really taking off. And that's regardless of what Dario Amodei is saying, which seems to confirm this. We're seeing releases of the latest iterations monthly, and once again: Qwen 3.5 has shown that China's open source is now only a few months behind Frontier Labs. Sam Altman recently said in India that the internal models had even exceeded his expectations and that he and we are unprepared for what's to come. Therefore, this should be taken seriously. GPT-5.4 was a complete success, just like Opus 4.6 shortly before it. We're still in Q1 2026, and everyone is saying that the upcoming models will be significantly better.

“The more you use AI, the more confident you’ll become in leveraging those tools”

Starlink now available in Kuwait!

You don't need a 9-5 JOB. You need this SKILL If you learn AI automation, you can charge: - $500-5k/mo to build automated workflows for businesses - $1-3k/mo to automate lead generation systems - $500-2k/mo for AI-powered content pipelines - $1-4k/mo to automate customer support with AI agents - $500-2k/mo for automated reporting & data dashboards - $500-2k/mo for AI-powered cold outreach systems - $1-3k/mo to set up internal automation assistants - $500-1.5k for AI workflow training for teams - $300-1k for 1:1 automation consulting the best that YOU'RE EARLY!!! 310M of 360M companies still DON'T have any automation and that doesn't even include things like automated research, CRM automation, meeting summaries, onboarding flows, etc. these are real business use cases, things that companies and potential clients actually need if this tweet gets 400+ likes ❤️, i'll publish a full article with a 0-6 month step-by-step playbook on what you should learn to start making money with AI automation it's not an easy path, but in my opinion, it's better than spending 4 years in university btw, based on the future guide, I could build my own product "Close AI" which already generates me $4k MRR (and we're not even launched lol) it literally closes the whole BD departments and partly Sales one since we wrote own LLM model (not Claude), studied it based on huge datasets + thousands of selling calls it's your turn.

When you chose a school for your kids, you probably didn't realize you were choosing educational software, but that choice of software might be more consequential for your kid than the choice of school. moultano.wordpress.com/2026/…

I deeply agree with Emily Bender's main point: LLMs are useless, unless you want to offload cognition. (The other two usecases she suggests are rare special cases of the third.) Offloading cognition into machines has always been the purpose and application of computer science and AI.

The U.S. has a weird cultural relationship with AI Despite the fact that we’ve driven the vast majority of AI breakthroughs, we still rank among the lowest countries in terms of consumer trust (Data from Edelman 2025 study) 👇

The U.S. has a weird cultural relationship with AI Despite the fact that we’ve driven the vast majority of AI breakthroughs, we still rank among the lowest countries in terms of consumer trust (Data from Edelman 2025 study) 👇

🚨BREAKING: Yale just published a study proving that AI chatbots are now better at changing your political views than professional campaign ads. Not slightly better. Significantly better. Across every major political issue tested. Two preregistered experiments. 19,145 participants. Seven frontier AI models from Anthropic, OpenAI, Google, and xAI. All of them outperformed standard political campaign advertisements at shifting how people vote. And it gets specific. Claude was the most persuasive model of all. Grok was the least. Every model in between beat the ads your government, parties, and campaigns spend billions of dollars producing every election cycle. Here is why this is different from every other AI persuasion study before it. Previous academic research said LLMs were roughly as persuasive as normal campaign methods. That became the accepted consensus. Politicians and regulators used it to argue that AI was not a special threat to elections. This study used far larger samples and tested the newest frontier models. The old consensus is now wrong. The researchers warn that as people increasingly treat AI as a neutral information source, anyone who gains control over how these systems respond to political questions can run a mass persuasion campaign at a scale no election law was ever written to address. Think about what you actually do. You ask ChatGPT who to vote for. You ask it to explain a policy. You ask it whether a candidate is trustworthy. You treat it like a search engine with judgment. It is not neutral. It was never neutral. And it is now provably better at moving your political beliefs than a campaign professional with a full budget and a media team. You are not consuming political ads. You think you are doing research. That is exactly what makes this work.

Holy shit. The guy who BUILT Claude Code just shared his actual workflow. Boris Cherny runs 10-15 Claude sessions in parallel every single day. While you're prompting one AI, he has 5 in his terminal + 5-10 on the web all shipping code simultaneously. And the real weapon? His CLAUDE.md file. Every time Claude makes a mistake, the team adds a rule so it NEVER happens again. Boris literally said: "After every correction, end with: Update your CLAUDE.md so you don't make that mistake again." Claude writes rules for itself. The longer you use it, the smarter it gets on YOUR codebase. His other insane detail: he hasn't written a single line of SQL in 6+ months. Claude just pulls BigQuery data directly via CLI. Claude Code now accounts for 4% of ALL public GitHub commits. Engineers who haven't set this up yet are already behind. This CLAUDE.md template is the difference between using AI as a chatbot vs using it as a fleet of senior engineers. Drop it in any project. Free.

How AI empowered Paul Conyngham to create a custom mRNA vaccine to cure his dog’s cancer when she had only months to live. The first personalized cancer vaccine designed for a dog: