Midjourney v7 Introduces Enhanced Image Quality and Precision Reference

Midjourney has rolled out v7 of its image generation model, sharpening image quality and refining prompt fidelity. The update improves renderings of hands and bodies—longstanding trouble spots—and adds tools like “Vary,” “Upscale,” and an enhanced image preview for smoother editing. A brand new –exp parameter lets users fine-tune aesthetics, though cranking it up may trade off some prompt precision. Intelligent segmentation features have also been added to streamline post-generation tweaks.

The launch of Omni-Reference expands creative control, letting users anchor specific elements—whether characters, objects, or vehicles—inside their images. With its “omni-weight” slider (0–1000), creators can dial in how strictly the model follows a reference, from loose style matching to high-fidelity replication.

While still experimental, Omni-Reference hints at a deeper push toward granular customization in image generation. Read more.

Meta is ramping up its AI agenda with recent data collection methods and deeper automation. Within the U.S., Ray-Ban smart glasses now default to recording user voices, funneling data into Meta’s AI systems to refine algorithmic performance. Opt-outs require disabling voice control or manually deleting recordings, triggering fresh privacy debates despite Meta’s claims of user control.

Alongside this, Mark Zuckerberg confirmed a forthcoming paid tier for the Meta AI app—approaching 1 billion users—offering enhanced compute and advanced features, mirroring moves by rivals. Meta also announced a sweeping overhaul of its ad business: advertisers now set objectives, and AI handles the whole lot from creative production to targeting and performance tracking. While pitched as “infinite creative,” the model is already stirring backlash over brand safety and trust in ad measurements. Read more.

DeepSeek has quietly dropped Prover-V2, a 671B-parameter open-source AI built for theorem proving and informal maths reasoning. Released on Hugging Face with little noise, Prover-V2 clocks 88.9% on the MiniF2F benchmark and uses a ‘cold-start’ method to interrupt down complex proofs into subgoals before formal verification.

The model, based on DeepSeek’s V3 foundation and mixture-of-experts architecture, sharpens mathematical precision inside its stack—despite DeepSeek’s limited access to Nvidia’s top-tier chips. Read more.

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