How Do You Build a Learner-Centered Ecosystem? — from gettingsmart.com by Bobbi Macdonald and Alin Bennett

Key Points

  • It’s not just about redesigning public education—it’s about rethinking how, where and with whom learning happens. Communities across the United States are shaping learner-centered ecosystems and gathering insights along the way.
  • What does it take to build a learner-centered ecosystem? A shared vision. Distributed leadership. Place-based experiences.  Repurposed resources. And more. This piece unpacks 10 real-world insights from pilots in action.
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We believe the path forward is through the cultivation of learner-centered ecosystems — adaptive, networked structures that offer a transformed way of organizing, supporting, and credentialing community-wide learning. These ecosystems break down barriers between schools, communities, and industries, creating flexible, real-world learning experiences that tap into the full range of opportunities a community has to offer.

Last year, we announced our Learner-Centered Ecosystem Lab, a collaborative effort to create a community of practice consisting of twelve diverse sites across the country — from the streets of Brooklyn to the mountains of Ojai — that are demonstrating or piloting ecosystemic approaches. Since then, we’ve been gathering together, learning from one another, and facing the challenges and opportunities of trying to transform public education. And while there is still much more work to be done, we’ve begun to observe a deeper pattern language — one that aligns with our ten-point Ecosystem Readiness Framework, and one that, we hope, can help all communities start to think more practically and creatively about how to transform their own systems of learning.

So while it’s still early, we suspect that the way to establish a healthy learner-centered ecosystem is by paying close attention to the following ten conditions:

 

 

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI — from papers.ssrn.com by Barbara Oakley, Michael Johnston, Kenzen Chen, Eulho Jung, and Terrence Sejnowski; via George Siemens

Abstract
In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities.
This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.

Keywords
cognitive offloading, memory, neuroscience of learning, declarative memory, procedural memory, generative AI, Flynn Effect, education reform, schemata, digital tools, cognitive load, cognitive architecture, reinforcement learning, basal ganglia, working memory, retrieval practice, schema theory, manifolds

 

“The AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
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How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course. 


How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.


In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.


Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.




AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.


What can we do about generative AI in our teaching?  — from linkedin.com by Kristina Peterson

So what can we do?

  • Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
  • Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
  • Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.

In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

 

The 2025 Global Skills Report— from coursera.org
Discover in-demand skills and credentials trends across 100+ countries and six regions to deliver impactful industry-aligned learning programs.

GenAI adoption fuels global skill demands
In 2023, early adopters flocked to GenAI, with approximately one person per minute enrolling in a GenAI course on Coursera —a rate that rose to eight per minute in 2024.  Since then, GenAI has continued to see exceptional growth, with global enrollment in GenAI courses surging 195% year-over-year—maintaining its position as one of the most rapidly growing skill domains on our platform. To date, Coursera has recorded over 8 million GenAI enrollments, with 12 learners per minute signing up for GenAI content in 2025 across our catalog of nearly 700 GenAI courses.

Driving this surge, 94% of employers say they’re likely to hire candidates with GenAI credentials, while 75% prefer hiring less-experienced candidates with GenAI skills over more experienced ones without these capabilities.8 Demand for roles such as AI and Machine Learning Specialists is projected to grow by up to 40% in the next four years.9 Mastering AI fundamentals—from prompt engineering to large language model (LLM) applications—is essential to remaining competitive in today’s rapidly evolving economy.

Countries leading our new AI Maturity Index— which highlights regions best equipped to harness AI innovation and translate skills into real-world applications—include global frontrunners such as Singapore, Switzerland, and the United States.

Insights in action

Businesses
Integrate role-specific GenAI modules into employee development programs, enabling teams to leverage AI for efficiency and innovation.

Governments
Scale GenAI literacy initiatives—especially in emerging economies—to address talent shortages and foster human-machine capabilities needed to future-proof digital jobs.

Higher education
Embed credit-eligible GenAI learning into curricula, ensuring graduates enter the workforce job-ready.

Learners
Focus on GenAI courses offering real-world projects (e.g., prompt engineering) that help build skills for in-demand roles.

 
 


Also relevant/see:


Report: 93% of Students Believe Gen AI Training Belongs in Degree Programs — from campustechnology.com by Rhea Kelly

The vast majority of today’s college students — 93% — believe generative AI training should be included in degree programs, according to a recent Coursera report. What’s more, 86% of students consider gen AI the most crucial technical skill for career preparation, prioritizing it above in-demand skills such as data strategy and software development. And 94% agree that microcredentials help build the essential skills they need to achieve career success.

For its Microcredentials Impact Report 2025, Coursera surveyed more than 1,200 learners and 1,000 employers around the globe to better understand the demand for microcredentials and their impact on workforce readiness and hiring trends.


1 in 4 employers say they’ll eliminate degree requirements by year’s end — from hrdive.com by Carolyn Crist
Companies that recently removed degree requirements reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.

A quarter of employers surveyed said they will remove bachelor’s degree requirements for some roles by the end of 2025, according to a May 20 report from Resume Templates.

In addition, 7 in 10 hiring managers said their company looks at relevant experience over a bachelor’s degree while making hiring decisions.

In the survey of 1,000 hiring managers, 84% of companies that recently removed degree requirements said it has been a successful move. Companies without degree requirements also reported a surge in applications, a more diverse applicant pool and the ability to offer lower salaries.


Why AI literacy is now a core competency in education — from weforum.org by Tanya Milberg

  • Education systems must go beyond digital literacy and embrace AI literacy as a core educational priority.
  • A new AI Literacy Framework (AILit) aims to empower learners to navigate an AI-integrated world with confidence and purpose.
  • Here’s what you need to know about the AILit Framework – and how to get involved in making it a success.

Also from Allison Salisbury, see:

 

How To Get Hired During the AI Apocalypse — from kathleendelaski.substack.com by Kathleen deLaski
And other discussions to have with your kids on the way to college graduation

A less temporary, more existential threat to the four year degree: AI could hollow out the entry level job market for knowledge workers (i.e. new college grads). And if 56% of families were saying college “wasn’t worth it” in 2023,(WSJ), what will that number look like in 2026 or beyond? The one of my kids who went to college ended up working in a bike shop for a year-ish after graduation. No regrets, but it came as a shock to them that they weren’t more employable with their neuroscience degree.

A colleague provided a great example: Her son, newly graduated, went for a job interview as an entry level writer last month and he was asked, as a test, to produce a story with AI and then use that story to write a better one by himself. He would presumably be judged on his ability to prompt AI and then improve upon its product. Is that learning how to DO? I think so. It’s using AI tools to accomplish a workplace task.


Also relevant in terms of the job search, see the following gifted article:

‘We Are the Most Rejected Generation’ — from nytimes.com by David Brooks; gifted article
David talks admissions rates for selective colleges, ultra-hard to get summer internships, a tough entry into student clubs, and the job market.

Things get even worse when students leave school and enter the job market. They enter what I’ve come to think of as the seventh circle of Indeed hell. Applying for jobs online is easy, so you have millions of people sending hundreds of applications each into the great miasma of the internet, and God knows which impersonal algorithm is reading them. I keep hearing and reading stories about young people who applied to 400 jobs and got rejected by all of them.

It seems we’ve created a vast multilayered system that evaluates the worth of millions of young adults and, most of the time, tells them they are not up to snuff.

Many administrators and faculty members I’ve spoken to are mystified that students would create such an unforgiving set of status competitions. But the world of competitive exclusion is the world they know, so of course they are going to replicate it. 

And in this column I’m not even trying to cover the rejections experienced by the 94 percent of American students who don’t go to elite schools and don’t apply for internships at Goldman Sachs. By middle school, the system has told them that because they don’t do well on academic tests, they are not smart, not winners. That’s among the most brutal rejections our society has to offer.


Fiverr CEO explains alarming message to workers about AI — from iblnews.org
Fiverr CEO Micha Kaufman recently warned his employees about the impact of artificial intelligence on their jobs.

The Great Career Reinvention, and How Workers Can Keep Up — from workshift.org by Michael Rosenbaum

A wide range of roles can or will quickly be replaced with AI, including inside sales representatives, customer service representatives, junior lawyers, junior accountants, and physicians whose focus is diagnosis.


Behind the Curtain: A white-collar bloodbath — from axios.com by Jim VandeHei and Mike Allen

Dario Amodei — CEO of Anthropic, one of the world’s most powerful creators of artificial intelligence — has a blunt, scary warning for the U.S. government and all of us:

  • AI could wipe out half of all entry-level white-collar jobs — and spike unemployment to 10-20% in the next one to five years, Amodei told us in an interview from his San Francisco office.
  • Amodei said AI companies and government need to stop “sugar-coating” what’s coming: the possible mass elimination of jobs across technology, finance, law, consulting and other white-collar professions, especially entry-level gigs.

Why it matters: Amodei, 42, who’s building the very technology he predicts could reorder society overnight, said he’s speaking out in hopes of jarring government and fellow AI companies into preparing — and protecting — the nation.

 

Skilling Up for AI Transformation — from learningguild.com by Lauren Milstid and Megan Torrance

Lately, I’ve been in a lot of conversations—some casual, some strategy-deep—about what it takes to skill up teams for AI. One pattern keeps emerging: The organizations getting the most out of generative AI are the ones doing the most to support their people. They’re not just training on a single tool. They’re building the capacity to work with AI as a class of technology.

So let’s talk about that. Not the hype, but the real work of helping humans thrive in an AI-enabled workplace.


If Leadership Training Isn’t Applied, It Hasn’t Happened — from learningguild.com by Tim Samuels

L&D leadership training sessions often “feel” successful. A program is designed, a workshop is delivered, and employees leave feeling informed and engaged. But if that training isn’t applied in the workplace, did it actually happen? If we focus entirely on the “learning” but not the “development,” we’re wasting huge amounts of time and money. So let’s take a look at the current situation first.

The reality is stark; according to Harvard Business Review:

  • Only 12% of employees apply new skills learned in L&D programs
  • Just 25% believe their training measurably improved performance
  • We forget 75% of what we learn within six days unless we use it
 

Opinions | This Baltimore program shows how to fight generational poverty – from washingtonpost.com by Leana S. Wen; this is a gifted article
How one grassroots organization is teaching young people leadership skills and giving them hope.

She recognized their desperation and felt called to return and use what she had learned to help them realize a different future. So she set up an organization, HeartSmiles, to do just that — one young person at a time.

Holifield’s experience is one that city officials and public health workers can learn from. If they want to disrupt the generational cycle of poverty, trauma and hopelessness that afflicts so many communities, a good place to focus their efforts is children.

How can communities overcome inertia and resignation? Holifield’s organization starts with two core interventions. The first is career and leadership development. Children as young as 8 go to the HeartSmiles center to participate in facilitated sessions on youth entrepreneurship, budgeting and conflict resolution. Those who want to explore certain career paths are matched with professionals in these fields.

The second part of her vision is youth-led mentorship, which involves pairing young people with those not much older than they are. 


Also relevant/see:

Lost boys, trapped men, and the role of lifers in prison education — from college-inside.beehiiv.com by Charlotte West

This week, we’re publishing Part 2 of a Q&A with Erik Maloney, a lifer in Arizona, and Kevin Wright, a criminal justice professor at Arizona State University. They co-authored Imprisoned Minds, a book about trauma and healing published in December 2024, over the course of seven years. Check out Part 1 of the Q&A.

West: The fact that you created your own curriculum to accompany the book makes me think about the role of lifers in creating educational opportunities in prisons. What do you see as the role of lifers in filling some of these gaps?

Maloney
: I’ve said for years that lifers are so underutilized in prison. It’s all about punishment for what you’re in for, and [the prison system] overlooks us as a resource. We are people who, if allowed to be educated properly, can teach courses indefinitely while also being a role model for those with shorter sentences. This gives the lifer meaning and purpose to do good again. He serves as a mentor, whether he likes it or not, to [those] people coming into the prisons. When they see him doing well, it inspires others to want to do well.

But if it’s all about punishment, and a person has no meaning and no purpose in life, then all they have is hopelessness. With hopelessness comes despair, and with despair, you have rampant drug and alcohol abuse in prison, and violence stems from that.

 

Making AI Work: Leadership, Lab, and Crowd — from oneusefulthing.org by Ethan Mollick
A formula for AI in companies

How do we reconcile the first three points with the final one? The answer is that AI use that boosts individual performance does not naturally translate to improving organizational performance. To get organizational gains requires organizational innovation, rethinking incentives, processes, and even the nature of work. But the muscles for organizational innovation inside companies have atrophied. For decades, companies have outsourced this to consultants or enterprise software vendors who develop generalized approaches that address the issues of many companies at once. That won’t work here, at least for a while. Nobody has special information about how to best use AI at your company, or a playbook for how to integrate it into your organization.
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Galileo Learn™ – A Revolutionary Approach To Corporate Learning — from joshbersin.com

Today we are excited to launch Galileo Learn™, a revolutionary new platform for corporate learning and professional development.

How do we leverage AI to revolutionize this model, doing away with the dated “publishing” model of training?

The answer is Galileo Learn, a radically new and different approach to corporate training and professional development.

What Exactly is Galileo Learn™?
Galileo Learn is an AI-native learning platform which is tightly integrated into the Galileo agent. It takes content in any form (PDF, word, audio, video, SCORM courses, and more) and automatically (with your guidance) builds courses, assessments, learning programs, polls, exercises, simulations, and a variety of other instructional formats.


Designing an Ecosystem of Resources to Foster AI Literacy With Duri Long — from aialoe.org

Centering Public Understanding in AI Education
In a recent talk titled “Designing an Ecosystem of Resources to Foster AI Literacy,” Duri Long, Assistant Professor at Northwestern University, highlighted the growing need for accessible, engaging learning experiences that empower the public to make informed decisions about artificial intelligence. Long emphasized that as AI technologies increasingly influence everyday life, fostering public understanding is not just beneficial—it’s essential. Her work seeks to develop a framework for AI literacy across varying audiences, from middle school students to adult learners and journalists.

A Design-Driven, Multi-Context Approach
Drawing from design research, cognitive science, and the learning sciences, Long presented a range of educational tools aimed at demystifying AI. Her team has created hands-on museum exhibits, such as Data Bites, where learners build physical datasets to explore how computers learn. These interactive experiences, along with web-based tools and support resources, are part of a broader initiative to bridge AI knowledge gaps using the 4As framework: Ask, Adapt, Author, and Analyze. Central to her approach is the belief that familiar, tangible interactions and interfaces reduce intimidation and promote deeper engagement with complex AI concepts.

 

I’m a LinkedIn Executive. I See the Bottom Rung of the Career Ladder Breaking. — from nytimes.com by Aneesh Raman; this is a gifted article

There are growing signs that artificial intelligence poses a real threat to a substantial number of the jobs that normally serve as the first step for each new generation of young workers. Uncertainty around tariffs and global trade is likely to only accelerate that pressure, just as millions of 2025 graduates enter the work force.

Breaking first is the bottom rung of the career ladder. In tech, advanced coding tools are creeping into the tasks of writing simple code and debugging — the ways junior developers gain experience. In law firms, junior paralegals and first-year associates who once cut their teeth on document review are handing weeks of work over to A.I. tools to complete in a matter of hours. And across retailers, A.I. chatbots and automated customer service tools are taking on duties once assigned to young associates.

 

Talk to Me: NVIDIA and Partners Boost People Skills and Business Smarts for AI Agents  — from blogs.nvidia.com by Adel El Hallak
NVIDIA Enterprise AI Factory validated design and latest NVIDIA AI Blueprints help businesses add intelligent AI teammates that can speak, research and learn to their daily operations.

Call it the ultimate proving ground. Collaborating with teammates in the modern workplace requires fast, fluid thinking. Providing insights quickly, while juggling webcams and office messaging channels, is a startlingly good test, and enterprise AI is about to pass it — just in time to provide assistance to busy knowledge workers.

To support enterprises in boosting productivity with AI teammates, NVIDIA today introduced a new NVIDIA Enterprise AI Factory validated design at COMPUTEX. IT teams deploying and scaling AI agents can use the design to build accelerated infrastructure and easily integrate with platforms and tools from NVIDIA software partners.

NVIDIA also unveiled new NVIDIA AI Blueprints to aid developers building smart AI teammates. Using the new blueprints, developers can enhance employee productivity through adaptive avatars that understand natural communication and have direct access to enterprise data.


NVIDIA CEO Envisions AI Infrastructure Industry Worth ‘Trillions of Dollars’ — from blogs.nvidia.com by Brian Caulfield
In his COMPUTEX keynote, Huang unveiled a sweeping vision for an AI-powered future, showcasing new platforms and partnerships.

“AI is now infrastructure, and this infrastructure, just like the internet, just like electricity, needs factories,” Huang said. “These factories are essentially what we build today.”

“They’re not data centers of the past,” Huang added. “These AI data centers, if you will, are improperly described. They are, in fact, AI factories. You apply energy to it, and it produces something incredibly valuable, and these things are called tokens.”

More’s coming, Huang said, describing the growing power of AI to reason and perceive. That leads us to agentic AI — AI able to understand, think and act. Beyond that is physical AI — AI that understands the world. The phase after that, he said, is general robotics.


Everything Revealed at Nvidia’s 2025 Computex Press Conference in 19 Minutes — from mashable.com
Nvidia is creating Omniverse Digital Twins of factories including humanoid robots

Watch all the biggest announcements from Nvidia’s keynote address at Computex 2025 in Taipei, Taiwan.


Dell unveils new AI servers powered by Nvidia chips to boost enterprise adoption — from reuters.com

May 19 (Reuters) – Dell Technologies (DELL.N), opens new tab on Monday unveiled new servers powered by Nvidia’s (NVDA.O), opens new tab Blackwell Ultra chips, aiming to capitalize on the booming demand for artificial intelligence systems.

The servers, available in both air-cooled and liquid-cooled variations, support up to 192 Nvidia Blackwell Ultra chips but can be customized to include as many as 256 chips.


Nvidia announces humanoid robotics, custom AI infrastructure tech at Computex 2025 — from finance.yahoo.com by Daniel Howley

Nvidia (NVDA) rolled into this year’s Computex Taipei tech expo on Monday with several announcements, ranging from the development of humanoid robots to the opening up of its high-powered NVLink technology, which allows companies to build semi-custom AI servers with Nvidia’s infrastructure.

During the event on Monday, Nvidia revealed its Nvidia Isaac GR00T-Dreams, which the company says helps developers create enormous amounts of training data they can use to teach robots how to perform different behaviors and adapt to new environments.


Addendums on 5/22/25:


 

‘What I learned when students walked out of my AI class’ — from timeshighereducation.com by Chris Hogg
Chris Hogg found the question of using AI to create art troubled his students deeply. Here’s how the moment led to deeper understanding for both student and educator

Teaching AI can be as thrilling as it is challenging. This became clear one day when three students walked out of my class, visibly upset. They later explained their frustration: after spending years learning their creative skills, they were disheartened to see AI effortlessly outperform them at the blink of an eye.

This moment stuck with me – not because it was unexpected, but because it encapsulates the paradoxical relationship we all seem to have with AI. As both an educator and a creative, I find myself asking: how do we engage with this powerful tool without losing ourselves in the process? This is the story of how I turned moments of resistance into opportunities for deeper understanding.


In the AI era, how do we battle cognitive laziness in students? — from timeshighereducation.com by Sean McMinn
With the latest AI technology now able to handle complex problem-solving processes, will students risk losing their own cognitive engagement? Metacognitive scaffolding could be the answer, writes Sean McMinn

The concern about cognitive laziness seems to be backed by Anthropic’s report that students use AI tools like Claude primarily for creating (39.8 per cent) and analysing (30.2 per cent) tasks, both considered higher-order cognitive functions according to Bloom’s Taxonomy. While these tasks align well with advanced educational objectives, they also pose a risk: students may increasingly delegate critical thinking and complex cognitive processes directly to AI, risking a reduction in their own cognitive engagement and skill development.


Make Instructional Design Fun Again with AI Agents — from drphilippahardman.substack.com by Dr. Philippa Hardman
A special edition practical guide to selecting & building AI agents for instructional design and L&D

Exactly how we do this has been less clear, but — fuelled by the rise of so-called “Agentic AI” — more and more instructional designers ask me: “What exactly can I delegate to AI agents, and how do I start?”

In this week’s post, I share my thoughts on exactly what instructional design tasks can be delegated to AI agents, and provide a step-by-step approach to building and testing your first AI agent.

Here’s a sneak peak….


AI Personality Matters: Why Claude Doesn’t Give Unsolicited Advice (And Why You Should Care) — from mikekentz.substack.com by Mike Kentz
First in a four-part series exploring the subtle yet profound differences between AI systems and their impact on human cognition

After providing Claude with several prompts of context about my creative writing project, I requested feedback on one of my novel chapters. The AI provided thoughtful analysis with pros and cons, as expected. But then I noticed what wasn’t there: the customary offer to rewrite my chapter.

Without Claude’s prompting, I found myself in an unexpected moment of metacognition. When faced with improvement suggestions but no offer to implement them, I had to consciously ask myself: “Do I actually want AI to rewrite this section?” The answer surprised me – no, I wanted to revise it myself, incorporating the insights while maintaining my voice and process.

The contrast was striking. With ChatGPT, accepting its offer to rewrite felt like a passive, almost innocent act – as if I were just saying “yes” to a helpful assistant. But with Claude, requesting a rewrite required deliberate action. Typing out the request felt like a more conscious surrender of creative agency.


Also re: metacognition and AI, see:

In the AI era, how do we battle cognitive laziness in students? — from timeshighereducation.com by Sean McMinn
With the latest AI technology now able to handle complex problem-solving processes, will students risk losing their own cognitive engagement? Metacognitive scaffolding could be the answer, writes Sean McMinn

The concern about cognitive laziness seems to be backed by Anthropic’s report that students use AI tools like Claude primarily for creating (39.8 per cent) and analysing (30.2 per cent) tasks, both considered higher-order cognitive functions according to Bloom’s Taxonomy. While these tasks align well with advanced educational objectives, they also pose a risk: students may increasingly delegate critical thinking and complex cognitive processes directly to AI, risking a reduction in their own cognitive engagement and skill development.

By prompting students to articulate their cognitive processes, such tools reinforce the internalisation of self-regulated learning strategies essential for navigating AI-augmented environments.


EDUCAUSE Panel Highlights Practical Uses for AI in Higher Ed — from govtech.com by Abby Sourwine
A webinar this week featuring panelists from the education, private and nonprofit sectors attested to how institutions are applying generative artificial intelligence to advising, admissions, research and IT.

Many higher education leaders have expressed hope about the potential of artificial intelligence but uncertainty about where to implement it safely and effectively. According to a webinar Tuesday hosted by EDUCAUSE, “Unlocking AI’s Potential in Higher Education,” their answer may be “almost everywhere.”

Panelists at the event, including Kaskaskia College CIO George Kriss, Canyon GBS founder and CEO Joe Licata and Austin Laird, a senior program officer at the Gates Foundation, said generative AI can help colleges and universities meet increasing demands for personalization, timely communication and human-to-human connections throughout an institution, from advising to research to IT support.


Partly Cloudy with a Chance of Chatbots — from derekbruff.org by Derek Bruff

Here are the predictions, our votes, and some commentary:

  • “By 2028, at least half of large universities will embed an AI ‘copilot’ inside their LMS that can draft content, quizzes, and rubrics on demand.” The group leaned toward yes on this one, in part because it was easy to see LMS vendors building this feature in as a default.
  • “Discipline-specific ‘digital tutors’ (LLM chatbots trained on course materials) will handle at least 30% of routine student questions in gateway courses.” We learned toward yes on this one, too, which is why some of us are exploring these tools today. We would like to be ready how to use them well (or avoid their use) when they are commonly available.
  • “Adaptive e-texts whose examples, difficulty, and media personalize in real time via AI will outsell static digital textbooks in the U.S. market.” We leaned toward no on this one, in part because the textbook market and what students want from textbooks has historically been slow to change. I remember offering my students a digital version of my statistics textbook maybe 6-7 years ago, and most students opted to print the whole thing out on paper like it was 1983.
  • “AI text detectors will be largely abandoned as unreliable, shifting assessment design toward oral, studio, or project-based ‘AI-resilient’ tasks.” We leaned toward yes on this. I have some concerns about oral assessments (they certainly privilege some students over others), but more authentic assignments seems like what higher ed needs in the face of AI. Ted Underwood recently suggested a version of this: “projects that attempt genuinely new things, which remain hard even with AI assistance.” See his post and the replies for some good discussion on this idea.
  • “AI will produce multimodal accessibility layers (live translation, alt-text, sign-language avatars) for most lecture videos without human editing.” We leaned toward yes on this one, too. This seems like another case where something will be provided by default, although my podcast transcripts are AI-generated and still need editing from me, so we’re not there quite yet.

‘We Have to Really Rethink the Purpose of Education’
The Ezra Klein Show

Description: I honestly don’t know how I should be educating my kids. A.I. has raised a lot of questions for schools. Teachers have had to adapt to the most ingenious cheating technology ever devised. But for me, the deeper question is: What should schools be teaching at all? A.I. is going to make the future look very different. How do you prepare kids for a world you can’t predict?

And if we can offload more and more tasks to generative A.I., what’s left for the human mind to do?

Rebecca Winthrop is the director of the Center for Universal Education at the Brookings Institution. She is also an author, with Jenny Anderson, of “The Disengaged Teen: Helping Kids Learn Better, Feel Better, and Live Better.” We discuss how A.I. is transforming what it means to work and be educated, and how our use of A.I. could revive — or undermine — American schools.


 

AI prompting secrets EXPOSED — from theneurondaily.com by Grant Harvey

Here are the three best prompting guides:

  • Anthropic’s “Prompt Engineering Overview is a free masterclass that’s worth its weight in gold. Their “constitutional AI prompting” section helped us create a content filter that actually works—unlike the one that kept flagging our coffee bean reviews as “inappropriate.” Apparently “rich body” triggered something…
  • OpenAI’s “Cookbook is like having a Michelin-star chef explain cooking—simple for beginners, but packed with pro techniques. Their JSON formatting examples saved us 3 hours of debugging last week…
  • Google’s “Prompt Design Strategies breaks down complex concepts with clear examples. Their before/after gallery showing how slight prompt tweaks improve results made us rethink everything we knew about getting quality outputs.

Pro tip: Save these guides as PDFs before they disappear behind paywalls. The best AI users keep libraries of these resources for quick reference.
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My personal review of 10+ AI agents and what actually works — from aiwithallie.beehiiv.com by Allie K. Miller
The AI Agents Report Card you wish your boss gave you.

What you’ll learn in this newsletter:

  • Which AI agents actually deliver value right now
  • Where even the best agents still fall embarrassingly short
  • The surprising truth about those sleek, impressive interfaces
  • The economics of delegating to AI (and when it’s worth the premium)
  • Five practical takeaways to guide your AI strategy

Employees Keep Their AI-Driven Productivity a Secret — from hrotoday.com; via The Neuron

“To address this, organizations should consider building a sustainable AI governance model, prioritizing transparency, and tackling the complex challenge of AI-fueled imposter syndrome through reinvention. Employers who fail to approach innovation with empathy and provide employees with autonomy run the risk of losing valuable staff and negatively impacting employee productivity.”  

Key findings from the report include the following:

  • Employees are keeping their productivity gains a secret from their employers. …
  • In-office employees may still log in remotely after hours. …
  • Younger workers are more likely to switch jobs to gain more flexibility.

AI discovers new math algorithms — from by Zach Mink & Rowan Cheung
PLUS: Anthropic reportedly set to launch new Sonnet, Opus models

The Rundown: Google just debuted AlphaEvolve, a coding agent that harnesses Gemini and evolutionary strategies to craft algorithms for scientific and computational challenges — driving efficiency inside Google and solving historic math problems.

Why it matters: Yesterday, we had OpenAI’s Jakub Pachocki saying AI has shown “significant evidence” of being capable of novel insights, and today Google has taken that a step further. Math plays a role in nearly every aspect of life, and AI’s pattern and algorithmic strengths look ready to uncover a whole new world of scientific discovery.


AI agents are set to explode: Reports forecast 45% annual growth rate — from hrexecutive.com by Jill Barth

At the recent HR Executive and Future Talent Council event at Bentley University near Boston, I talked with Top 100 HR Tech Influencer Joey Price about what he’s hearing from HR leaders. Price is president and CEO of Jumpstart HR and executive analyst at Aspect43, Jumpstart HR’s HR?tech research division, and author of a valuable new book, The Power of HR: How to Make an Organizational Impact as a People?Professional.

This puts him solidly at the center of HR’s most relevant conversations. Price described the curiosity he’s hearing from many HR leaders about AI agents, which have become increasingly prominent in recent months.


 

 

Stop Trying to Make Everyone Go to College — from nytimes.com by Randi Weingarten; this is a gifted article

For years, America’s approach to education has been guided by an overly simplistic formula: 4+4 — the idea that students need four years of high school and four years of college to succeed in life.

Even with this prevailing emphasis on college, around 40 percent of high schoolers do not enroll in college upon graduating, and only 60 percent of students who enroll in college earn a degree or credential within eight years of high school graduation.

While college completion has positive effects — on health, lifetime earnings, civic engagement and even happiness — it’s increasingly clear that college for all should no longer be our North Star. It’s time to scale up successful programs that create multiple pathways for students so high school is a gateway to both college and career.

I propose a different strategy: aligning high school to both college prep and in-demand vocational career pathways. Just as students who plan to go to college can get a head start through Advanced Placement programs, high schools, colleges and employers should work together to provide the relevant coursework to engage students in promising career opportunities.

 
© 2025 | Daniel Christian