🧠 You Can Now Tune ChatGPT’s Personality

ChatGPT is getting a bit more you. New personality controls and in-chat editing tools let you fine-tune how it sounds, from warmer and more enthusiastic to clean and straight to the point. Let’s dive in!

In today’s insights:

LATEST DEVELOPMENTS

Evolving AI: ChatGPT adds personality controls and smarter in-chat editing tools.

OpenAI is rolling out new personalization options that let users fine-tune how ChatGPT sounds and behaves. You can choose more or less warmth and enthusiasm, control emoji use, and tweak how often headers and lists appear. Users can pick preset personalities like professional or friendly. Email workflows are smoother too, with direct formatting inside chat and the ability to highlight text and request targeted edits without rewriting prompts.

People are starting to use ChatGPT like a daily coworker, and that only works if it can match your tone without you rewriting the same “be more formal” prompt all day. These new Characteristics controls let you set a default vibe once, then keep it consistent across chats, which is huge for email-heavy jobs where brand voice and “don’t sound weird” expectations are real. Pair that with in-chat text editing and highlight-to-rewrite, and you get fewer back-and-forth prompts and faster cleanups right where the draft lives. It’s the UI quietly catching up to how people already work: quick revisions, tight turnaround, consistent style.

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Evolving AI: Kling 2.6 adds voice and motion upgrades that push AI video closer to usable realism.

Kuaishou has rolled out two updates for Kling 2.6 focused on sound and movement. Voice control lets creators generate spoken dialogue, narration, singing, and scene audio directly inside text to video workflows. Users can upload a voice or train one for reuse across multiple clips. Motion control now handles fast actions and full body movement with cleaner hands, natural faces, and stable lip sync, using short motion reference videos and text prompts.

Voice and motion landing in the same model shows where AI video is heading: faster output that’s usable without heavy cleanup. When characters keep the same voice across clips and movement no longer breaks immersion, AI video shifts from a fun demo to a repeatable format for ads, explainers, news-style clips, and daily social posts. Add low per-second pricing and platforms that reward volume, and this starts to look less like experimentation and more like a new default for short-form production.

Evolving AI: Alibaba’s Qwen released an image model that splits photos into editable layers.

Alibaba’s Qwen team introduced Qwen-Image-Layered, an image editing model that breaks a single image into multiple transparent layers. Each layer can be edited on its own, making tasks like swapping backgrounds, replacing people, adjusting text, or changing object positions straightforward. The model supports 3 or 8 initial layers, and each layer can be split again for finer control. The code is open source, with models and demos available on GitHub, Hugging Face, and ModelScope, alongside a technical report.

Layer-based editing is how real design work gets done, and Qwen-Image-Layered brings that workflow to AI outputs: it decomposes a flat image into separate RGBA layers, so you can move the subject, swap the background, tweak text, or recolor an object without the rest of the scene breaking. For ad teams, e-commerce, and social content, that means faster “small changes” cycles and fewer reruns when a client asks for one tiny tweak. The fact it’s open-weight and ships with code, model weights, and live demos makes it easy to plug into existing pipelines and tools people already use.

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