#ChatBot

Let’s talk money. Literally. ChatGPT Voice has come to Finances. Securely connect your accounts through Finances, then use Voice to talk spending, savings, and all the money questions on your mind. Try it:

We have a gif for you—ChatGPT Images 2.6 is here. ChatGPT Images 2.6 can turn your prompts and pictures into animated GIFs. You can also keep reference images of yourself, pets, and characters ready to reuse in new creations...no need to upload them again. Go on. Make it weird. Send more GIFs of your dog dancing. Images 2.6 is available today in ChatGPT, and Codex across all tiers on web, desktop, and mobile.

Your teammate built a great site. Naturally, you have notes. With Remix, make your own version of a site by telling ChatGPT what you'd like to change. Then keep editing your copy in chat. Now rolling out to ChatGPT Business and Enterprise accounts.

For AGI to benefit all of humanity, it should help people with the everyday tasks that matter most to them. So we built LifeVal, a new benchmark shaped by feedback from thousands of ChatGPT users on where they most want help from a personal assistant—from finding childcare to accessing government services to managing personal finances. Over the past year, we’ve used LifeVal to measure and improve how well our models handle these everyday tasks.

You can earn $9000 a month if you have ChatGPT, a laptop, internet, and 1 hour a day. I usually charge $93 for this guide, but today it's yours 100% free. Like + reply 'Money' & I'll send you my full guide for FREE. Must follow me to receive guide in DM Free for 48 hours

chatgpt images 2.6 is here!

Images, upgraded—introducing ChatGPT Images 2.6. Now with GIFs and reference images. Plus, two new models are coming to the API with 50% faster image generation.

GIFS! With ChatGPT Images 2.6, turn a prompt or image into an animated GIF. Adjust the speed, edit individual frames, and share it on repeat.

ChatGPT and Codex are helping engineers build for the physical world. We’re sharing our progress across mechanical design, electrical engineering, and simulation—from helping our hardware teams iterate faster to testing new workflows with industry collaborators.

You can earn $7000/month if you have ChatGPT, a laptop, and 60 mins a day. Usually, I'd charge $79 for this guide, but today you get it completely free. Like + reply 'Money' and I'll send you my detailed guide for FREE. Must follow me to get guide in your DM. FREE for 48 hrs.

Wild stat. We are now generate more than 4B images per week across ChatGPT and the API, up from the more than 3B per week only 8 weeks ago.

I wrote a step-by-step GUIDE on how I make $4,900 a week using ChatGPT, working just a few hours a day. Normally, this guide sells for $139, but today you get it 100% FREE. Like + Comment "Guide" and I'll DM it to you. Must follow me to get DM. FREE for next 48 hours.

The GPT-Image 2.6 is a game changer for AI video generation, when combined with Minimax H3. I made a full 15 sec video by: 1. Creating a 15 sec animated GIF on ChatGPT 2. Feeding it to H3 (via Maestro) Animated GIF on the left. Final video on the right. Workflow in thread 👇

holy sh*t, someone just mapped 51,000+ paid AI apps you can reverse engineer today chatbots, writing tools, coding assistants and image apps, and most builders have no idea it’s free the drop: → (51,000+ AI tools · 9,000+ companies) the index itself: every AI app you can pick from, the list of wrappers worth looking inside → (143.9k ★ · 34.8k forks) system prompts, internal tools and model info from Cursor, Claude Code, Devin, Windsurf, Replit, Lovable and Perplexity → (62.7k ★ · 10.3k forks) publicly extracted prompts from Anthropic, OpenAI, Google, xAI, Microsoft, Perplexity, Meta, Mistral, DeepSeek and Cursor → (51.6k ★ · 10.5k forks) extracted instructions of ChatGPT, Claude, Gemini, Grok and Perplexity → (15.0k ★ · 2.1k forks) a collection of leaked system prompts from widely used AI services → (116 prompts · 33 companies) the same kind of collection, readable in your browser → the formula: pick an AI tool you pay for → read its public prompt → let REA show what it really calls → rebuild it or stop paying

REA hit #1 on GitHub trending, and most people still run it inside a single chat Split it into 4 subagents and one command takes a program you own from sealed binary to a tested rebuild with a match rate Set it up once, aim it at the next one:

$6 press releases are hacking ChatGPT, Perplexity, and Google. “ Best AI SEO newsletter for CMOs,” ChatGPT  says SEO Espresso.  Perplexity  says the same.   Google's AI Overviews  say the same.  All platforms  cite a $6 press release distributed  by AB Newswire.  AB Newswire charges $500  for 83 press releases.  $500 divided by 83 is $6. By the way, there's more crazy SEO like this with the Compact Keywords SEO course.  What happens next is lots of marketers will share one of these $500 packages, splitting the cost. And that is how $6 press releases are hacking ChatGPT, Perplexity, and Google.

I don't understand how so many people are still using only ChatGPT and Claude. These 9 tools are taking over in 2026, and almost nobody is talking about them:

Sam Altman (CEO of Open AI): "You no longer need to write prompts." In just 38 minutes, he explains how to use ChatGpt at a level that most people can't even imagine. It's talk he gave to stanford students. A friend sent me the recording last night. After watching it, I realized I was only taking advantage of about 15% of what this tool can really do. Watch it in full and then read the guide l leave below on how to create a system that prompts itself.

🚨Leave Netflix tonight. Watch this 2 h 34 min Stanford class. It's the clearest, most complete, and brutally honest explanation out there on how ChatGPT and Claude are really built. From Tokenization and BPE to the Transformer architecture, the training pipeline, and the next-token decoder. No fluff. No marketing. Just the truth. Doesn't matter if you've never touched a line of AI code or if you spend your days launching Agents: by the end, you'll suddenly connect a ton of pieces you've been trying to fit together for years. The real core boils down to this: How text turns into numbers the model can "eat" (BPE tokenization) The sole mission of a language model: predict the next token How the Transformer uses Attention so tokens can pass messages to each other In training, the NLL loss pushes the probability of the entire sequence In generation, the decoder builds the response token by token The big-picture view that takes most people years to form… this class delivers it to you complete in one sitting. Free up your time. This could be, no exaggeration, the most valuable class you watch this month.

Taking a fresh look at @ChatGPT mobile What works well? What takes too many clicks? What would you like to see?