#gpt-based-ai

#gpt-based-ai

Did you know you can teach ChatGPT how to respond to certain requests? Not only can you give ChatGPT instructions, but they'll stick (mostly) for every session. This feature is called Custom Instructions. It lives in the Personalization tab of ChatGPT's settings. In a minute, I'll show you a set of really powerful directives that can help make you super productive.

For every project that needs guardrails, there's another one where they just get in the way. Some projects demand an LLM that returns the complete, unvarnished truth. For these situations, developers are creating unfettered LLMs that can interact without reservation. Some of these solutions are based on entirely new models while others remove or reduce the guardrails built into popular open source LLMs.

The new model consolidates some of the capabilities that OpenAI had previously spread across separate models, bringing together the coding strengths of GPT-5.3-Codex-the company's leading programming model-improved reasoning skills, and the agentic ability for the model to navigate desktops, browsers, and software applications autonomously.

ChatGPT Pulse is a mobile AI feature for Pro users that delivers personalized updates and information directly in users' feeds. This new "push" approach gives brands an opportunity to reach audiences proactively, even before they search for content. To appear in ChatGPT Pulse, focus on building content that is authoritative, clear, and AI-ready. Establish verified brand profiles, maintain canonical pages, and publish regularly updated, time-stamped content.

AI Text Humanizer Protects Your Original Intent and Meaning Maintain your core perspective while restructuring sentence patterns. Humanizer ai accurately identifies and locks in technical terms, factual data, and key arguments, ensuring the rewritten draft is simply more readable without any semantic drift. You get a qualitative leap in flow and tone, allowing you to humanize ai text while keeping your original message perfectly intact.

A major difference between LLMs and LTMs is the type of data they're able to synthesize and use. LLMs use unstructured data-think text, social media posts, emails, etc. LTMs, on the other hand, can extract information or insights from structured data, which could be contained in tables, for instance. Since many enterprises rely on structured data, often contained in spreadsheets, to run their operations, LTMs could have an immediate use case for many organizations.

OpenAI's GPT-5.2 Pro does better at solving sophisticated math problems than older versions of the company's top large language model, according to a new study by Epoch AI, a non-profit research institute.