AI News
14,624 stories from 2538 sources · 1428 in the last 24 hours · refreshed hourly. Every story links to the original publisher.
Today's AI news from trusted publishers and official AI lab blogs, refreshed about every 30 minutes.
News today: 6,058Last updated:
- Beyond the Toggle Tax: A Design Principle for Friction-Free AISuperhuman · toolsA single work task is rarely confined to one place. For instance, a customer update might begin in a dashboard, take shape in a document, gather feedback in Slack, and reach its final audience through an email. Each individual tool supports part of the outcome, yet they are rarely connected.
- Scaling AI Responsibly: How Three Institutions Turned Adoption Into ImpactSuperhuman · toolsReal examples of AI in higher education. How three institutions built agents on Superhuman Go and made adoption stick.
- The Provost’s Case for Institution-Wide AISuperhuman · toolsAI in higher education has arrived on campus. See how academic leaders turn scattered faculty AI use into consistent, measurable student outcomes.
- The Trust Ladder: Why AI Adoption Should Be EarnedSuperhuman · toolsTrust grows when people can understand what AI is actually doing before they choose to ask it to do more. That progression rarely fits neatly into a yes-or-no decision tree. Instead, trusting AI to flag an unclear sentence, prepare a reply, and send a message without review grants
- What It Takes to Lead a College Through the AI ShiftSuperhuman · toolsJenny Maxwell, Head of Education at Superhuman, sat down with Timothy Moore, President of Indian River State College, to talk about what it takes to lead a college through this AI moment. Their lightly edited conversation is below. To learn more about Indian River s AI transformation, subscribe to
- A Look Into Superhuman’s New Hub in BerlinSuperhuman · toolsSuperhuman s Berlin team has moved into a new hub at Das Center at Potsdamer Platz, occupying a space once home to an IMAX cinema. After sitting closed for more than five years, it is beginning a new chapter as a place for our team to work, build, collaborate,
- Agent Orchestration at Scale: Lessons From Superhuman GoSuperhuman · toolsLearn how Superhuman Go scales AI tool routing across 100+ agents, why performance degrades as tools grow, and how embedded shortlisting improves accuracy.
- Grammarly’s Writing Agents Become Proactive With GoSuperhuman · toolsLearn how Superhuman Go enhances Grammarly's writing agents, making them proactive.
- The Collaboration Gap: AI Has a Teamwork ProblemSuperhuman · toolsAI made individuals faster, but teams are still stuck with tools built for a pre-AI world AI can help one person turn an idea into a draft, prototype, or presentation faster than ever before. The challenge starts the moment they try to share it. Most AI tools are built
- How We Built Barney, Superhuman’s Threat Hunter AI AgentSuperhuman · toolsLearn how Superhuman built Barney, an AI threat-hunting agent that helps security teams investigate more alerts, catch risks earlier, and scale their defenses.
- The “We Already Have AI” Objection: What It Takes to Adopt a New Tool for WorkSuperhuman · toolsA new AI tool rarely enters a company with a blank slate. It arrives after leaders have selected a platform, approved its security, allocated budget, and encouraged employees to use it. The existing tool already has a business case and organizational momentum. We saw the strength of that advantage in
- Built With Institutions: Takeaways from EDUCAUSE 2026Superhuman · toolsThe theme of EDUCAUSE 2026 was clear: the institutions making real progress with AI are building it with their own people. Three takeaways from our week in the room.
- Why Human Skills Matter More Than Ever in an AI EconomySuperhuman · toolsAlthough most professional trajectories aren t purely linear, a standard early-career path for knowledge workers has long existed. You graduate from college, start in an entry-level role, and build judgment and business context over time through experience and repeated routine tasks. But now AI is automating routine
- GPTZero is Now Part of Superhuman: What It Means for Signals of Authentic WorkSuperhuman · toolsBest-in-class AI detection now sits alongside Grammarly’s authorship tools inside Superhuman’s authenticity layer, giving instructors more reliable signals and students a fairer read on their work.
- Redesigning a College Around Generative AISuperhuman · toolsHow one college is redesigning around generative AI in higher education, and what building on Superhuman Go looks like for a peer institution.
- The Communication Challenge at the Heart of AI Adoption in Higher EducationSuperhuman · toolsby Bruce W. Fraser, Executive Director of AI Initiatives, Indian River State College Recently, I had a conversation about AI adoption with a colleague from another college in Florida. This person is responsible for AI training at her institution, and she is one of the brightest, most thoughtful leaders I&
- In the Age of AI, Writing Has an Authenticity ProblemSuperhuman · toolsA growing number of professionals are worried about being mistaken for a machine. AI slop is an imprecise cultural term for content that feels generic, careless, or mass-produced. The discomfort it describes often has less to do with a sentence s polish than with the sense
- How We Scaled Our LLM Inference Infrastructure to Serve 100+ Billion Requests a WeekSuperhuman · toolsHow Grammarly scaled real-time LLM inference to 100 billion requests per week — including how we evaluated external vendors, optimized for latency and cost, and our final hybrid architecture.
- The Learning-Visibility Loop: How AI Should Participate in EducationSuperhuman · toolsSuperhuman’s point of view on the ethical use of AI in higher education: the learning-visibility loop, a model that makes student learning visible to faculty.
- Research at Your Cursor: Building a Proactive Insights Agent on Superhuman GoSuperhuman · toolsDon t search for research. Let the right insights find you. Every company eventually encounters the same problem: it has more research insights than people can reasonably remember. A product manager writing a strategy may make a claim about what customers need while three existing studies complicate that assumption.
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