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LinkedIn Is Trying To Help You Apply For Fewer Jobs
The platform’s new AI-powered “Job Match” aims to guide users toward roles they’re qualified for and away from those they aren’t.
If you’ve ever spoken to anyone hunting for a job lately, you’ve probably heard about how difficult it is to even secure an interview. According to LinkedIn, one of the reasons for this struggle is that too many people are applying for roles they aren’t qualified for, making it harder for strong candidates to get noticed.
To tackle this, LinkedIn is rolling out a new AI-powered tool called “Job Match” — a feature designed to bridge the gap between job seekers and recruiters by offering detailed summaries that help users understand how well they fit a particular role.
Unlike simple keyword matching tools, “Job Match” takes a more nuanced approach by using AI to analyze a candidate’s overall experience and compare it with the qualifications listed in a job description. The idea isn’t just to help users find roles they’re qualified for, but also to steer them away from applying to jobs where they might fall short.
The feature is accessible to all LinkedIn users, but those with LinkedIn Premium get extra perks, such as more detailed insights about their job match level. In the future, recruiters will also benefit, as the tool aims to surface more qualified candidates, reducing the chances of strong applicants being overlooked.
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Whether this new approach will make life easier for job seekers is still up for debate. The last couple of years have been brutal for many industries, with massive layoffs still a regular occurrence at the start of 2025. All this means even fiercer competition for fewer openings — something no AI tool can ever hope to completely solve.
However, LinkedIn product manager Rohan Rajiv believes the lack of transparency in hiring is a big part of the issue, pointing out that early testing of “Job Match” showed that a “non-trivial chunk” of mismatches between candidates and jobs is easier to fix than people realize. “I think there’s a portion of this that will always be labor market dynamics, but I would argue that there’s a significant portion of this that is just pure lack of transparency,” he said.
News
Nano Banana 2 Arrives In MENA For Google Gemini Users
Google brings its latest image model to Gemini and Search, adding 4K output and tighter text control for regional users.
Google has opened access to Nano Banana 2 across the Middle East and North Africa, pushing its newest image model into everyday tools rather than keeping it inside the exclusive (and expensive) Pro tier.
The rollout spans the Google Gemini desktop and mobile apps, and extends to Google Search through Lens and AI Mode. Developers can also test it in preview via AI Studio and the Gemini API.
Nano Banana 2 runs on Gemini Flash, Google’s fast inference layer. The focus is speed, but also control. Users can export visuals from 512px up to 4K, adjusting aspect ratios for everything from vertical social posts to widescreen displays.
The model maintains character likeness across up to five figures and preserves fidelity for as many as 14 objects within a single workflow. This enables visual continuity across scenes, iterations, or edits — supporting projects like short films, storyboards, and multi-scene narratives. Text rendering has also been improved, delivering legible typography in mockups and greeting cards, with built-in translation and localization directly within images.
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Under the hood, the system taps Gemini’s broader knowledge base and pulls in real-time information and imagery from web search to render specific subjects more accurately. Lighting and fine detail have been upgraded, without slowing output.
By embedding the model inside Gemini and Search, Google is normalizing advanced image generation for a mass audience. In MENA, where startups and marketing teams are leaning heavily on AI to scale content across languages and borders, that shift lands at a practical moment.
The move also folds creative tooling deeper into search itself, so that image generation is no longer a separate workflow. It now sits right next to the query box.
