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LinkedIn’s New AI Tools Rethink How Job Seekers Discover Career Paths
By understanding intent, not just keywords, LinkedIn’s AI helps users find more meaningful job matches — even in roles they hadn’t considered.
LinkedIn is rolling out new AI-powered job search tools designed to match users with better career opportunities — whether or not they know exactly what they’re looking for.
The new features allow job seekers to describe their goals in natural language instead of relying on rigid keywords or exact job titles. Want to explore “business development in the video game industry” or “use your marketing skills to help fund cancer research”? LinkedIn’s AI now understands even the most abstract of intents and can recommend roles that align — even if job listings don’t use those specific terms.
“It’s about helping people express what they want to do in their own words,” said Rohan Rajiv, head of career products at LinkedIn. “Our AI figures out the semantics behind that and matches it with relevant opportunities”.
This evolution in job search is powered by large language models (LLMs), the same kind of AI that fuels tools like ChatGPT. These models excel at inferring meaning from both job descriptions and user profiles, identifying matches that traditional search engines might miss. For instance, the AI can assume a web developer is proficient in HTML, even if they haven’t explicitly listed it on their profile.
Another tool, called Job Match, assesses how well a user fits a role based on their skills and experience. It also pinpoints gaps — like missing certifications or limited exposure to a required technology — helping users better prepare before they apply.
LinkedIn’s AI also offers context around job listings, such as whether an employer is actively hiring, whether a role is promoted on the platform, and typical wait times between application and response.
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Erran Berger, LinkedIn’s VP of engineering, explained that recruiters are also overwhelmed: “They’re spending up to five hours a day filtering through applications, and over half don’t meet basic requirements”. The new AI features aim to improve quality on both sides, helping candidates apply more strategically and saving time for hiring teams.
With over 15 million job postings and 11,000 job applications submitted every minute on LinkedIn, these tools are a major step toward transforming a job market that often feels inefficient and transactional.
CEO Ryan Roslansky framed the update as part of LinkedIn’s long-term evolution: “Twenty years ago, we connected recruiters with passive candidates. Today, we’re using AI to redefine what’s possible in job discovery”.
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ESET Bets On Specialized Security AI At 0.5% The Training Cost
ESET says NeoCortex can estimate an attacker’s next move, with a kill switch and human oversight built in to keep it from going rogue.
A sign-in anomaly, a suspicious process launch and an unusual connection may look harmless alone. Together, they can describe an intrusion that is hard for security to teams to piece together.
To solve that problem, ESET announced ESET NeoCortex on November 4, 2026: a specialized foundational AI model for cybersecurity. It powers ESET LiveCortex, available within the ESET PROTECT Platform, which connects fragmented security signals and turns them into actionable incidents.
Filtering is the main selling point, with LiveCortex processing billions of raw telemetry events daily, and just 0.00111% of them contributing to incidents presented to customers. The aim is less alert fatigue and more analyst time spent on threats that matter.
NeoCortex is built on world-model architecture, learning how digital environments behave and how events relate. ESET says that lets it reconstruct missing incident context, recognize similar past cases and estimate an attacker’s likely next step – what the company calls “minus-one-day defense,” a chance to intervene before the next stage unfolds. ESET points to Black October, the week leading up to October 25, 2026, when critical security issues affecting PHP, Linux, GitLab and other key systems demanded rapid, prioritized responses, as the kind of moment where that context matters.
ESET’s internal research also suggests a specialized model like NeoCortex can be trained at up to 200 times lower cost than a large general reasoning model, while delivering more accurate, defense-focused results. The company credits optimized training, a focus on cybersecurity vocabulary, lower computing requirements and privately owned hardware.
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“AI is accelerating both cyberattacks and cyberdefenses. With ESET NeoCortex, we are applying our AI investment to develop specialized foundational cybersecurity intelligence that remains under our control and strengthens, rather than replaces, human expertise,” said Juraj Malcho, Chief Technology Officer at ESET.
As part of the design, NeoCortex forms part of a layered architecture combining specialized models, deterministic controls, correlation logic, validation, auditability and expert human oversight. Safeguards include restricted sandboxes, read-only tools, continuous monitoring, defined usage and token limits, a kill switch and human oversight of critical response decisions. The model is also developed and self-hosted on ESET’s own infrastructure, which the company says reduces exposure to shifts among third-party AI providers, including commercial and geopolitical ones.
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