The Campus AI Crisis — by Jeffrey Selingo; via Ryan Craig Young graduates can’t find jobs. Colleges know they have to do something. But what?
Only now are colleges realizing that the implications of AI are much greater and are already outrunning their institutional ability to respond. As schools struggle to update their curricula and classroom policies, they also confront a deeper problem: the suddenly enormous gap between what they say a degree is for and what the labor market now demands.In that mismatch, students are left to absorb the risk. Alina McMahon and millions of other Gen-Zers like her are caught in a muddled in-between moment: colleges only just beginning to think about how to adapt and redefine their mission in the post-AI world, and a job market that’s changing much, much faster.
“Colleges and universities face an existential issue before them,” said Ryan Craig, author of Apprentice Nation and managing director of a firm that invests in new educational models. “They need to figure out how to integrate relevant, in-field, and hopefully paid work experience for every student, and hopefully multiple experiences before they graduate.”
Character consistency, native audio, 15-second generations & first results
Image & Video Prompts
Imagine Art 1.5 Pro, Genspark AI Workspace 2.0 & PixVerse Real-Time Video Workflows
Kling 3.0: Everyone a Director
Kling just dropped version 3.0, and it’s a legitimate leap forward for AI video production (Kling is the GOAT). After spending early access time testing the new capabilities, I can confirm this is the most significant update to video generation tools I’ve seen in months.
Jim VandeHei’s note to his kids: Blunt AI talk — from axios.com by CEO Jim VandeHei Axios CEO Jim VandeHei wrote this note to his wife, Autumn, and their three kids. She suggested sharing it more broadly since so many families are wrestling with how to think and talk about AI. So here it is …
Dear Family: I want to put to words what I’m hearing, seeing, thinking and writing about AI.
Simply put, I’m now certain it will upend your work and life in ways more profound than the internet or possibly electricity. This will hit in months, not years.
The changes will be fast, wide, radical, disorienting and scary. No one will avoid its reach.
I’m not trying to frighten you. And I know your opinions range from wonderment to worry. That’s natural and OK. Our species isn’t wired for change of this speed or scale.
My conversations with the CEOs and builders of these LLMs, as well as my own deep experimentation with AI, have shaken and stirred me in ways I never imagined.
All of you must figure out how to master AI for any specific job or internship you hold or take. You’d be jeopardizing your future careers by not figuring out how to use AI to amplify and improve your work. You’d be wise to replace social media scrolling with LLM testing.
The Essential Retrieval Practice Handbook — from edutopia.org Retrieval practice is one of the most effective ways to strengthen learning. Here’s a collection of our best resources to use in your classroom today.
January 29, 2026
When we think about learning, we typically focus on getting information into students’ heads. What if, instead, we focus on getting information out of students’ heads?
What if the biggest change in education isn’t a new app… but the end of the university monopoly on credibility?
Jensen Huang has framed AI as a platform shift—an industrial revolution that turns intelligence into infrastructure. And when intelligence becomes cheap, personal, and always available, education stops being a place you go… and becomes a system that follows you. The question isn’t whether universities will disappear. The question is whether the old model—high cost, slow updates, one-size-fits-all—can survive a world where every student can have a private tutor, a lab partner, and a curriculum designer on demand.
This video explores what AI has in store for education—and why traditional universities may need to reinvent themselves fast.
In this video you’ll discover:
How AI tutors could deliver personalized learning at scale
Why credentials may shift from “degrees” to proof-of-skill portfolios
What happens when the “middle” of studying becomes automated
How universities could evolve: research hubs, networks, and high-trust credentialing
The risks: cheating, dependency, bias, and widening inequality
The 3 skills that become priceless when information is everywhere: judgment, curiosity, and responsibility
From DSC:
There appears to be another, similar video, but with a different date and length of the video. So I’m including this other recording as well here:
What if universities don’t “disappear”… but lose their monopoly on learning, credentials, and opportunity?
AI is turning education into something radically different: personal, instant, adaptive, and always available. When every student can have a 24/7 tutor, a writing coach, a coding partner, and a study plan designed specifically for them, the old model—one professor, one curriculum, one pace for everyone—starts to look outdated. And the biggest disruption isn’t the classroom. It’s the credential. Because in an AI world, proof of skill can become more valuable than a piece of paper.
This video explores the end of universities as we know them: what AI is bringing, what will break, what will survive, and what replaces the traditional path.
In this video you’ll discover:
Why AI tutoring could outperform one-size-fits-all lectures
How “degrees” may shift into skill proof: portfolios, projects, and verified competency
What happens when the “middle” of studying becomes automated
How universities may evolve: research hubs, networks, high-trust credentialing
The dark side: cheating, dependency, inequality, and biased evaluation
The new advantage: judgment, creativity, and responsibility in a world of instant answers
Penelope Adams Moon suggested that instead [of] framing a workshop around “How can we integrate AI into the work of teaching?” we should ask “Given what we know about learning, how might AI be useful?” I love that reframing, and I think it connects to the students’ requests for more AI knowhow. Students have a lot of options for learning: working with their instructor, collaborating with peers, surfing YouTube for explainer videos, university-provided social annotation platforms, and, yes, using AI as a kind of tutor. I think our job (collectively) isn’t just to teach students how to use AI (as they’re requesting) but also to help them figure out when and how AI is helpful for their learning. That’s highly dependent on the student and the learning task! I wrote about this kind of metacognition on my blog.
In the same way, when I approach any kind of educational technology, I’m looking for tools that can be responsive to my pedagogical aims. The pedagogy should drive the technology use, not the other way around.
The real story isn’t what AI can produce — it’s how it changes the decisions we make at every stage of instructional design.
After working with thousands of instructional designers on my bootcamp, I’ve learned something counterintuitive: the best teams aren’t the ones with the fanciest AI tools — they’re the ones who know when to use which mode—and when to use none at all.
Once you recognise that, you start to see instructional design differently — not as a linear process, but as a series of decision loops where AI plays distinct roles.
In this post, I show you the 3 modes of AI that actually matter in instructional design — and map them across every phase of ADDIE so you know exactly when to let AI run, and when to slow down and think.
In higher education, developing strong multiple-choice questions can be a time-intensive part of the course design process. Developing such items requires subject-matter expertise and assessment literacy, and for faculty and designers who are creating and producing online courses, it can be difficult to find the capacity to craft quality multiple-choice questions.
At the University of Michigan Center for Academic Innovation, learning experience designers are using generative artificial intelligence to streamline the multiple-choice question development process and help ameliorate this issue. In this article, I summarize one of our projects that explored effective prompting strategies to develop multiple-choice questions with ChatGPT for our open course portfolio. We examined how structured prompting can improve the quality of AI-generated assessments, producing relevant comprehension and recall items and options that include plausible distractors.
Achieving this goal enables us to develop several ungraded practice opportunities, preparing learners for their graded assessments while also freeing up more time for course instructors and designers.
Is click-to-reveal always bad for learning? Not necessarily. Click-to-reveal interactions can be useful when you want to manage cognitive load, reveal information gradually, or work within limited screen space. In those cases, clicking supports the presentation of information.
However, from an instructional perspective, clicking alone does not make an interaction meaningful. An interaction adds value when it asks learners to think, not just trigger more content.
The interaction ideas below require learners to analyze, judge, predict, or diagnose. These are the types of mental actions learners perform in real work settings. Each one includes a short, real-world question to show how the idea might be used in practice.
At CES 2026, Everything Is AI. What Matters Is How You Use It — from wired.com by Boone Ashworth Integrated chatbots and built-in machine intelligence are no longer standout features in consumer tech. If companies want to win in the AI era, they’ve got to hone the user experience.
Beyond Wearables
Right now, AI is on your face and arms—smart glasses and smart watches—but this year will see it proliferate further into products like earbuds, headphones, and smart clothing.
Health tech will see an influx of AI features too, as companies aim to use AI to monitor biometric data from wearables like rings and wristbands. Heath sensors will also continue to show up in newer places like toilets, bath mats, and brassieres.
The smart home will continue to be bolstered by machine intelligence, with more products that can listen, see, and understand what’s happening in your living space. Familiar candidates for AI-powered upgrades like smart vacuums and security cameras will be joined by surprising AI bedfellows like refrigerators and garage door openers.
After a year of bot battles, one thing stands out: There is no single best AI. The smartest way to use chatbots today is to pick different tools for different jobs — and not assume one bot can do it all.
Some enterprise platforms now support cross-agent communication and integration with ecosystems maintained by companies like Microsoft, NVIDIA, Google, and Oracle. These cross-platform data fabrics break down silos and turn isolated AI pilots into enterprise-wide services. The result is an IT backbone that not only automates but also collaborates for continuous learning, diagnostics, and system optimization in real time.
It’s difficult to think of any single company that had a bigger impact on Wall Street and the AI trade in 2025 than Nvidia (NVDA).
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Nvidia’s revenue soared in 2025, bringing in $187.1 billion, and its market capitalization continued to climb, briefly eclipsing the $5 trillion mark before settling back in the $4 trillion range.
There were plenty of major highs and deep lows throughout the year, but these 15 were among the biggest moments of Nvidia’s 2025.
Work from home jobs with no experience can help you earn money from home, even if you are new and have never done a remote job before. If you are looking for work from home jobs with no experience and aren’t sure which are real (and worth your time), you’re in the right place. In this guide, you will find real, beginner-friendly remote jobs you can do from home, even if you have never worked remotely before.
We will explain the best entry-level options, what they may pay, what you need to get started, and how to avoid scams. I will also share simple tips to help you get work-from-home jobs with no experience and start remote jobs faster.
… 1) What is the best work from home with no experience?
The best work-from-home jobs with no experience are usually remote customer service, transcription, AI task work, or moderation, since training and guidelines are provided.
2) What jobs can you do online from home with no experience?
You can do online customer support, transcription/captioning, microtasks, paid research studies, and entry-level AI evaluation tasks.
