What are colleges’ legal options when threatened with federal funding cuts? — from highereddive.com/ by Lilah Burke
Higher education experts said colleges could work together or lean on their associations if they take up a legal fight against the Trump administration.

Understand your allies
In fact, colleges may struggle to fight the administration on their own.

“I don’t think that institutions should necessarily fight it by themselves,” said Jeffrey Sun, a higher education and law professor at the University of Louisville. “I don’t think they’ll win.”

What will have more power is several institutions, or even many, working together to fight the attacks on higher education.

“I don’t think we have an option unless we work in collective action,” Sun said.


Harvard University won’t yield to Trump administration’s demands— from highereddive.com by Natalie Schwartz
Alan Garber, the Ivy League institution’s president, said the university wouldn’t forfeit its “independence or its constitutional rights.”

Harvard University President Alan Garber said Monday that officials there would not yield to the Trump administration’s litany of demands to maintain access to federal funding, arguing the federal government had overstepped its authority by issuing the ultimatum. 

“The University will not surrender its independence or relinquish its constitutional rights,” Garber wrote in a community message

The move tees up a battle between the Ivy League institution and the Trump administration, which threatened the university with the loss of $9 billion in federal funding over what it claimed was a failure to protect Jewish students from antisemitism.


Harvard Professors Sue the Trump Administration While Other Universities Are Targeted — from iblnews.org

Two groups representing Harvard University professors (the American Association of University Professors and the Harvard faculty chapter) filed a lawsuit against the Trump Administration on Friday, saying that the threat to cut billions in federal funding for the institution violates free speech and other First Amendment rights.

The Trump Administration announced two weeks ago that it reviewed about $9 billion in federal funding that Harvard receives and would send a list of demands to unfreeze the money.

In a statement, Andrew Manuel Crespo, a law professor at Harvard and general counsel of the AAUP-Harvard Faculty Chapter, said the “Trump administration’s policies are a pretext to chill universities and their faculties from engaging in speech, teaching, and research that don’t align with President Trump’s views.”


OPINION: For our republic to survive, education leaders must remain firm in the face of authoritarianism — from hechingerreport.org by Jason E. Glass
We face direct threats to the values around access, opportunity and truth our schools are meant to uphold

Across the country, education leaders are being forced to make some tough decisions — to choose between defending core values, such as equity and historical truth, or yielding to political coercion in hopes of avoiding conflict. There is no strategy that does not involve conflict and trade-offs. Every education leader operates in their own political context with unique legal and cultural constraints.

But make no mistake: Inaction is not neutral. Even the decision to do nothing is a choice, one that has consequences.


Northwestern to self-fund federally threatened research — from highereddive.com by Laura Spitalniak
Leaders at the well-known institution said the support would sustain “vital research” until they had a “better understanding of the funding landscape.”

Northwestern University will pull from its coffers to continue funding “vital research” that has been threatened by the Trump administration, the private institution announced Thursday.


Trump is bullying, blackmailing and threatening colleges, and they are just beginning to fight back — from hechingerreport.org by Liz Willen
After Harvard rejected the president’s demands, more university leaders have started to speak out — but many say a bigger response is needed

Many hope it is the beginning of a new resistance in higher education. “Harvard’s move gives others permission to come out on the ice a little,” McGuire said. “This is an answer to the tepid and vacillating presidents who said they don’t want to draw attention to themselves.”

Harvard paved the way for other institutions to stand up to the administration’s demands, Ted Mitchell, president of the American Council on Education, noted in an interview with NPR this week.

Stanford University President Jonathan Levin immediately backed Harvard, noting that “the way to bring about constructive change is not by destroying the nation’s capacity for scientific research, or through the government taking command of a private institution.”

“I tell them, you will never regret doing what is right, but if you allow yourself to be co-opted, you will have regret that you caved to a dictator who doesn’t care about you or your institution.”

 

How People Are Really Using Gen AI in 2025 — from hbr.org by Marc Zao-Sanders

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Here’s why you shouldn’t let AI run your company — from theneurondaily.com by Grant Harvey; emphasis DSC

When “vibe-coding” goes wrong… or, a parable in why you shouldn’t “vibe” your entire company.
Cursor, an AI-powered coding tool that many developers love-to-hate, face-planted spectacularly yesterday when its own AI support bot went off-script and fabricated a company policy, leading to a complete user revolt.

Here’s the short version:

  • A bug locked Cursor users out when switching devices.
  • Instead of human help, Cursor’s AI support bot confidently told users this was a new policy (it wasn’t).
  • No human checked the replies—big mistake.
  • The fake news spread, and devs canceled subscriptions en masse.
  • A Reddit thread about it got mysteriously nuked, fueling suspicion.

The reality? Just a bug, plus a bot hallucination… doing maximum damage.

Why it matters: This is what we’d call “vibe-companying”—blindly trusting AI with critical functions without human oversight.

Think about it like this: this was JUST a startup. If more big corporations continue to lay off entire departments, replaced by AI, these already byzantine companies will become increasingly more opaque, unaccountable systems where no one, human or AI, fully understands what’s happening or who’s responsible.

Our take? Kafka dude has it right. We need to pay attention to WHAT we’re actually automating. Because automating more bureaucracy at scale, with agents we increasingly don’t understand or don’t double check, can potentially make companies less intelligent—and harder to fix when things inevitably go wrong.


 

 

Thomson Reuters Survey: Over 95% of Legal Professionals Expect Gen AI to Become Central to Workflow Within Five Year — from lawnext.com by Bob Ambrogi

Thomson Reuters today released its 2025 Generative AI in Professional Services Report, and it reveals that legal professionals have become increasingly optimistic about generative AI, with adoption rates nearly doubling over the past year and a growing belief that the technology should be incorporated into legal work.

According to the report, 26% of legal organizations are now actively using gen AI, up from 14% in 2024. While only 15% of law firm respondents say gen AI is currently central to their workflow, a striking 78% believe it will become central within the next five years.


AI-Powered Legal Work Redefined: Libra Launches Major Update for Legal Professionals — from lawnext.com by Bob Ambrogi

Berlin, April 14, 2025 – Berlin-based Legal Tech startup Libra is launching its most comprehensive update to date, leveraging AI to relieve law firms and legal departments of routine tasks, accelerate research, and improve team collaboration. “Libra v2” combines highly developed AI, a modern user interface, and practical tools to set a new standard for efficient and precise work in all legal areas.

“We listened intently to feedback from law firms and in-house teams,” said Viktor von Essen, founder of Libra. “The result is Libra v2: an AI solution that intelligently supports every step of daily legal work – from initial research to final contract review. We want legal experts to be able to fully concentrate on what is essential: excellent legal advice.”


The Three Cs of Teaching Technology to Law Students — from lawnext.com by Bob Ambrogi

In law practice today, technology is no longer optional — it’s essential. As practicing attorneys increasingly rely on technology tools to serve clients, conduct research, manage documents and streamline workflows, the question is often debated: Are law schools adequately preparing students for this reality?

Unfortunately, for the majority of law schools, the answer is no. But that only begs the question: What should they be doing?

A coincidence of events last week had me thinking about law schools and legal tech, chief among them my attendance at LIT Con, Suffolk Law School’s annual conference to showcase legal innovation and technology — with a portion of it devoted to access-to-justice projects developed by Suffolk Law students themselves.


While not from Bob, I’m also going to include this one here:

Your AI Options: 7 Considerations Before You Buy — from artificiallawyer.com by Liza Pestillos-Ocat

But here’s the problem: not all AI is useful and not all of it is built for the way your legal team works.

Most firms aren’t asking whether they should use AI because they already are. The real question now is what comes next? How do you expand the value of AI across more teams, more matters, and more workflows without introducing unnecessary risk, complexity, or cost?

To get this right, legal professionals need to understand which tools will solve real problems and deliver the most value to their team. That starts with asking better questions, including the ones that follow, before making your next investment in AI for lawyers.

 

The 2025 AI Index Report — from Stanford University’s Human-Centered Artificial Intelligence Lab (hai.stanford.edu); item via The Neuron

Top Takeaways

  1. AI performance on demanding benchmarks continues to improve.
  2. AI is increasingly embedded in everyday life.
  3. Business is all in on AI, fueling record investment and usage, as research continues to show strong productivity impacts.
  4. The U.S. still leads in producing top AI models—but China is closing the performance gap.
  5. The responsible AI ecosystem evolves—unevenly.
  6. Global AI optimism is rising—but deep regional divides remain.
  7. …and several more

Also see:

The Neuron’s take on this:

So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.

Just keep two big things in mind:

  1. Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
  2. Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.

So, use the tools, find what helps you, but don’t trust them completely.

We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.


Addendum on 4/16:

 

Essential AI tools for better work — from wondertools.substack.com by Jeremy Caplan
My favorite tactics for making the most of AI — a podcast conversation

AI tools I consistently rely on (areas covered mentioned below)

  • Research and analysis
  • Communication efficiency
  • Multimedia creation

AI tactics that work surprisingly well 

1. Reverse interviews
Instead of just querying AI, have it interview you. Get the AI to interview you, rather than interviewing it. Give it a little context and what you’re focusing on and what you’re interested in, and then you ask it to interview you to elicit your own insights.”

This approach helps extract knowledge from yourself, not just from the AI. Sometimes we need that guide to pull ideas out of ourselves.


OpenAI’s Deep Research Agent Is Coming for White-Collar Work — from wired.com by Will Knight
The research-focused agent shows how a new generation of more capable AI models could automate some office tasks.

Isla Fulford, a researcher at OpenAI, had a hunch that Deep Research would be a hit even before it was released.

Fulford had helped build the artificial intelligence agent, which autonomously explores the web, deciding for itself what links to click, what to read, and what to collate into an in-depth report. OpenAI first made Deep Research available internally; whenever it went down, Fulford says, she was inundated with queries from colleagues eager to have it back. “The number of people who were DMing me made us pretty excited,” says Fulford.

Since going live to the public on February 2, Deep Research has proven to be a hit with many users outside the company too.


Nvidia to open quantum computing research center in Boston — from seekingalpha.com by Ravikash Bakolia

Nvidia (NASDAQ:NVDA) will open a quantum computing research lab in Boston which is expected to start operations later this year.

The Nvidia Accelerated Quantum Research Center, or NVAQC, will integrate leading quantum hardware with AI supercomputers, enabling what is known as accelerated quantum supercomputing, said the company in a March 18 press release.

Nvidia’s CEO Jensen Huang also made this announcement on Thursday at the company’s first-ever Quantum Day at its annual GTC event.


French quantum computer firm Pasqal links up with NVIDIA — from reuters.com

PARIS, March 21 (Reuters) – Pasqal, a fast-growing French quantum computer start-up company, announced on Friday a partnership with chip giant Nvidia (NVDA.O), opens new tab whereby Pasqal’s customers would gain access to more tools to develop quantum applications.

Pasqal said it would connect its quantum computing units and cloud platform onto NVIDIA’s open-source platform called CUDA-Q.


Introducing next-generation audio models in the API — from openai.com
A new suite of audio models to power voice agents, now available to developers worldwide.

Today, we’re launching new speech-to-text and text-to-speech audio models in the API—making it possible to build more powerful, customizable, and intelligent voice agents that offer real value. Our latest speech-to-text models set a new state-of-the-art benchmark, outperforming existing solutions in accuracy and reliability—especially in challenging scenarios involving accents, noisy environments, and varying speech speeds. These improvements increase transcription reliability, making the models especially well-suited for use cases like customer call centers, meeting note transcription, and more.


 

8 Weeks Left to Prepare Students for the AI-Enhanced Workplace — from insidehighered.com by Ray Schroeder
We are down to the final weeks left to fully prepare students for entry into the AI-enhanced workplace. Are your students ready?

The urgent task facing those of us who teach and advise students, whether they be degree program or certificate seeking, is to ensure that they are prepared to enter (or re-enter) the workplace with skills and knowledge that are relevant to 2025 and beyond. One of the first skills to cultivate is an understanding of what kinds of services this emerging technology can provide to enhance the worker’s productivity and value to the institution or corporation.

Given that short period of time, coupled with the need to cover the scheduled information in the syllabus, I recommend that we consider merging AI use into authentic assignments and assessments, supplementary modules, and other resources to prepare for AI.


Learning Design in the Era of Agentic AI — from drphilippahardman.substack.com by Dr Philippa Hardman
Aka, how to design online async learning experiences that learners can’t afford to delegate to AI agents

The point I put forward was that the problem is not AI’s ability to complete online async courses, but that online async courses courses deliver so little value to our learners that they delegate their completion to AI.

The harsh reality is that this is not an AI problem — it is a learning design problem.

However, this realisation presents us with an opportunity which we overall seem keen to embrace. Rather than seeking out ways to block AI agents, we seem largely to agree that we should use this as a moment to reimagine online async learning itself.



8 Schools Innovating With Google AI — Here’s What They’re Doing — from forbes.com by Dan Fitzpatrick

While fears of AI replacing educators swirl in the public consciousness, a cohort of pioneering institutions is demonstrating a far more nuanced reality. These eight universities and schools aren’t just experimenting with AI, they’re fundamentally reshaping their educational ecosystems. From personalized learning in K-12 to advanced research in higher education, these institutions are leveraging Google’s AI to empower students, enhance teaching, and streamline operations.


Essential AI tools for better work — from wondertools.substack.com by Jeremy Caplan
My favorite tactics for making the most of AI — a podcast conversation

AI tools I consistently rely on (areas covered mentioned below)

  • Research and analysis
  • Communication efficiency
  • Multimedia creation

AI tactics that work surprisingly well 

1. Reverse interviews
Instead of just querying AI, have it interview you. Get the AI to interview you, rather than interviewing it. Give it a little context and what you’re focusing on and what you’re interested in, and then you ask it to interview you to elicit your own insights.”

This approach helps extract knowledge from yourself, not just from the AI. Sometimes we need that guide to pull ideas out of ourselves.

 

Introducing NextGenAI: A consortium to advance research and education with AI — from openai.com; via Claire Zau
OpenAI commits $50M in funding and tools to leading institutions.

Today, we’re launching NextGenAI, a first-of-its-kind consortium with 15 leading research institutions dedicated to using AI to accelerate research breakthroughs and transform education.

AI has the power to drive progress in research and education—but only when people have the right tools to harness it. That’s why OpenAI is committing $50M in research grants, compute funding, and API access to support students, educators, and researchers advancing the frontiers of knowledge.

Uniting institutions across the U.S. and abroad, NextGenAI aims to catalyze progress at a rate faster than any one institution would alone. This initiative is built not only to fuel the next generation of discoveries, but also to prepare the next generation to shape AI’s future.


 ‘I want him to be prepared’: why parents are teaching their gen Alpha kids to use AI — from theguardian.com by Aaron Mok; via Claire Zau
As AI grows increasingly prevalent, some are showing their children tools from ChatGPT to Dall-E to learn and bond

“My goal isn’t to make him a generative AI wizard,” White said. “It’s to give him a foundation for using AI to be creative, build, explore perspectives and enrich his learning.”

White is part of a growing number of parents teaching their young children how to use AI chatbots so they are prepared to deploy the tools responsibly as personal assistants for school, work and daily life when they’re older.

 

Blind Spot on AI — from the-job.beehiiv.com by Paul Fain
Office tasks are being automated now, but nobody has answers on how education and worker upskilling should change.

Students and workers will need help adjusting to a labor market that appears to be on the verge of a historic disruption as many business processes are automated. Yet job projections and policy ideas are sorely lacking.

The benefits of agentic AI are already clear for a wide range of organizations, including small nonprofits like CareerVillage. But the ability to automate a broad range of business processes means that education programs and skills training for knowledge workers will need to change. And as Chung writes in a must-read essay, we have a blind spot with predicting the impacts of agentic AI on the labor market.

“Without robust projections,” he writes, “policymakers, businesses, and educators won’t be able to come to terms with how rapidly we need to start this upskilling.”

 

You can now use Deep Research without $200 — from flexos.work


Accelerating scientific breakthroughs with an AI co-scientist — from research.google by Juraj Gottweis and Vivek Natarajan

We introduce AI co-scientist, a multi-agent AI system built with Gemini 2.0 as a virtual scientific collaborator to help scientists generate novel hypotheses and research proposals, and to accelerate the clock speed of scientific and biomedical discoveries.


Now decides next: Generating a new future — from Deloitte.com
Deloitte’s State of Generative AI in the Enterprise Quarter four report

There is a speed limit. GenAI technology continues to advance at incredible speed. However, most organizations are moving at the speed of organizations, not at the speed of technology. No matter how quickly the technology advances—or how hard the companies producing GenAI technology push—organizational change in an enterprise can only happen so fast.

Barriers are evolving. Significant barriers to scaling and value creation are still widespread across key areas. And, over the past year regulatory uncertainty and risk management have risen in organizations’ lists of concerns to address. Also, levels of trust in GenAI are still moderate for the majority of organizations. Even so, with increased customization and accuracy of models—combined with a focus on better governance— adoption of GenAI is becoming more established.

Some uses are outpacing others. Application of GenAI is further along in some business areas than in others in terms of integration, return on investment (ROI) and expectations. The IT function is most mature; cybersecurity, operations, marketing and customer service are also showing strong adoption and results. Organizations reporting higher ROI for their most scaled initiatives are broadly further along in their GenAI journeys.

 

AI in K12: Today’s Breakthroughs and Tomorrow’s Possibilities (webinar)
How AI is Transforming Classrooms Today and What’s Next


Audio-Based Learning 4.0 — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new & powerful way to leverage AI for learning?

At the end of all of this my reflection is that the research paints a pretty exciting picture – audio-based learning isn’t just effective, it’s got some unique superpowers when it comes to boosting comprehension, ramping up engagement, and delivering feedback that really connects with learners.

While audio has been massively under-used as a mode of learning, especially compared to video and text, we’re at an interesting turning point where AI tools are making it easier than ever to tap into audio’s potential as a pedagogical tool.

What’s super interesting is how the solid research backing audio’s effectiveness is and how well this is converging with these new AI capabilities.

From DSC:
I’ve noticed that I don’t learn as well via audio-only based events. It can help if visuals are also provided, but I have to watch the cognitive loads. My processing can start to get overloaded — to the point that I have to close my eyes and just listen sometimes. But there are people I know who love to listen to audiobooks and prefer to learn that way. They can devour content and process/remember it all. Audio is a nice change of pace at times, but I prefer visuals and reading often times. It needs to be absolutely quiet if I’m tackling some new information/learning. 


In Conversation With… Ashton Cousineau — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new video series exploring how L&D professionals are working with AI on the ground

In Conversation With… Ashton Cousineau by Dr Philippa Hardman

A new video series exploring how L&D professionals are working with AI on the ground

Read on Substack


The Learning Research Digest vol. 28 — from learningsciencedigest.substack.com by Dr. Philippa Hardman

Hot Off the Research Press This Month:

  • AI-Infused Learning Design – A structured approach to AI-enhanced assignments using a three-step model for AI integration.
  • Mathematical Dance and Creativity in STEAM – Using AI-powered motion capture to translate dance movements into mathematical models.
  • AI-Generated Instructional Videos – How adaptive AI-powered video learning enhances problem-solving and knowledge retention.
  • Immersive Language Learning with XR & AI – A new framework for integrating AI-driven conversational agents with Extended Reality (XR) for task-based language learning.
  • Decision-Making in Learning Design – A scoping review on how instructional designers navigate complex instructional choices and make data-driven decisions.
  • Interactive E-Books and Engagement – Examining the impact of interactive digital books on student motivation, comprehension, and cognitive engagement.
  • Elevating Practitioner Voices in Instructional Design – A new initiative to amplify instructional designers’ contributions to research and innovation.

Deep Reasoning, Agentic AI & the Continued Rise of Specialised AI Research & Tools for Education — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s a quick teaser of key developments in the world of AI & learning this month:

  • DeepSeek R-1, OpenAI’s Deep Seek & Perplexity’s ‘Deep Research’ are the latest additions to a growing number of “reasoning models” with interesting implications for evidence-based learning design & development.
  • The U.S. Education Dept release an AI Toolkit and a fresh policy roadmap enabling the adoption of AI use in schools.
  • Anthropic Release “Agentic Claude”, another AI agent that clicks, scrolls, and can even successfully complete e-learning courses…
  • Oxford University Announce the AIEOU Hub, a research-backed research lab to support research and implementation on AI in education.
  • “AI Agents Everywhere”: A Forbes peek at how agentic AI will handle the “boring bits” of classroom life.
  • [Bias klaxon!] Epiphany AI: My own research leads to the creation of a specialised, “pedagogy first” AI co-pilot for instructional design marking the continued growth of specialised AI tools designed for specific industries and workflows.

AI is the Perfect Teaching Assistant for Any Educator — from unite.ai by Navi Azaria, CPO at Kaltura

Through my work with leading educational institutions at Kaltura, I’ve seen firsthand how AI agents are rapidly becoming indispensable. These agents alleviate the mounting burdens on educators and provide new generations of tech-savvy students with accessible, personalized learning, giving teachers the support they need to give their students the personalized attention and engagement they deserve.


Learning HQ — from ai-disruptor-hq.notion.site

This HQ includes all of my AI guides, organized by tool/platform. This list is updated each time a new one is released, and outdated guides are removed/replaced over time.



How AI Is Reshaping Teachers’ Jobs — from edweek.org

Artificial intelligence is poised to fundamentally change the job of teaching. AI-powered tools can shave hours off the amount of time teachers spend grading, lesson-planning, and creating materials. AI can also enrich the lessons they deliver in the classroom and help them meet the varied needs of all students. And it can even help bolster teachers’ own professional growth and development.

Despite all the promise of AI, though, experts still urge caution as the technology continues to evolve. Ethical questions and practical concerns are bubbling to the surface, and not all teachers feel prepared to effectively and safely use AI.

In this special report, see how early-adopter teachers are using AI tools to transform their daily work, tackle some of the roadblocks to expanded use of the technology, and understand what’s on the horizon for the teaching profession in the age of artificial intelligence.

 

The Anthropic Economic Index — from anthropic.com; via George Siemens

In the coming years, AI systems will have a major impact on the ways people work. For that reason, we’re launching the Anthropic Economic Index, an initiative aimed at understanding AI’s effects on labor markets and the economy over time.

The Index’s initial report provides first-of-its-kind data and analysis based on millions of anonymized conversations on Claude.ai, revealing the clearest picture yet of how AI is being incorporated into real-world tasks across the modern economy.

We’re also open sourcing the dataset used for this analysis, so researchers can build on and extend our findings.

 

Half A Million Students Given ChatGPT As CSU System Makes AI History — from forbes.com by Dan Fitzpatrick

The California State University system has partnered with OpenAI to launch the largest deployment of AI in higher education to date.

The CSU system, which serves nearly 500,000 students across 23 campuses, has announced plans to integrate ChatGPT Edu, an education-focused version of OpenAI’s chatbot, into its curriculum and operations. The rollout, which includes tens of thousands of faculty and staff, represents the most significant AI deployment within a single educational institution globally.

We’re still in the early stages of AI adoption in education, and it is critical that the entire ecosystem—education systems, technologists, educators, and governments—work together to ensure that all students globally have access to AI and develop the skills to use it responsibly

Leah Belsky, VP and general manager of education at OpenAI.




HOW educators can use GenAI – where to start and how to progress — from aliciabankhofer.substack.com by Alicia Bankhofer
Part of 3 of my series: Teaching and Learning in the AI Age

As you read through these use cases, you’ll notice that each one addresses multiple tasks from our list above.

1. Researching a topic for a lesson
2. Creating Tasks For Practice
3. Creating Sample Answers
4. Generating Ideas
5. Designing Lesson Plans
6. Creating Tests
7. Using AI in Virtual Classrooms
8. Creating Images
9. Creating worksheets
10. Correcting and Feedback


 

Also see:

Introducing deep research — from openai.com
An agent that uses reasoning to synthesize large amounts of online information and complete multi-step research tasks for you. Available to Pro users today, Plus and Team next.

[On 2/2/25 we launched] deep research in ChatGPT, a new agentic capability that conducts multi-step research on the internet for complex tasks. It accomplishes in tens of minutes what would take a human many hours.

Deep research is OpenAI’s next agent that can do work for you independently—you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst.

Comments/information per The Rundown AI:
The Rundown: OpenAI just launchedDeep Research, a new ChatGPT feature that conducts extensive web research on complex topics and delivers detailed reports with citations in under 30 minutes.

The details:

  • The system uses a specialized version of o3 to analyze text, images, and PDFs across multiple sources, producing comprehensive research summaries.
  • Initial access is limited to Pro subscribers ($200/mo) with 100 queries/month, but if safety metrics remain stable, it will expand to Plus and Team users within weeks.
  • Research tasks take between 5-30 minutes to complete, with users receiving a list of clarifying questions to start and notifications when results are ready.
  • Deep Research achieved a 26.6% on Humanity’s Last Exam, significantly outperforming other AI models like Gemini Thinking (6.2%) and GPT-4o (3.3%).

Why it matters: ChatGPT excels at quick, instant answers, but Deep Research represents the first major consumer attempt at tackling complex tasks that take humans days. Combined with the release of Operator, the landscape is shifting towards longer thinking with autonomous actions — and better results to show for it.

Also see:

The End of Search, The Beginning of OpenAI’s Deep Research — from theaivalley.com by Barsee

The quality of citations are also genuinely advance. Unlike traditional AI-generated sources prone to hallucinations, Deep Research provides legitimate academic references. Clicking a citation often takes users directly to the relevant highlighted text.

In a demo, the agent generated a comprehensive report on iOS and Android app market trends, showcasing its ability to tackle intricate subjects with accuracy.


Top 13 AI insights — from theneurondaily.com

Which links to and discusses Andrej Karpathy’s video at:

.

.

This is a general audience deep dive into the Large Language Model (LLM) AI technology that powers ChatGPT and related products. It is covers the full training stack of how the models are developed, along with mental models of how to think about their “psychology”, and how to get the best use them in practical applications. I have one “Intro to LLMs” video already from ~year ago, but that is just a re-recording of a random talk, so I wanted to loop around and do a lot more comprehensive version.

 

Five things to know before you launch a research podcast — from timeshighereducation.com by David Allan  and Andrew Murray
Starting a podcast can open up your research to a new audience. David Allan and Andrew Murray show how

Launching a podcast isn’t necessarily difficult. Sustaining it, on the other hand, is difficult. You’re entering a crowded market – it’s estimated that there are more than 4 million of them – and audience share is far from equal. An alarmingly high number fail to make it past their third episode before being scrapped, and the vast majority put out fewer than 20 episodes.

Despite these challenges, podcasts can be an astonishingly effective tool to promote research or academic knowledge. If you avoid the many pitfalls, you have a communication tool with full control of the message; a tool that exists in perpetuity, drawing attention to the work that you do.

Here, a highly experienced podcast producer and associate lecturer at the University of the West of Scotland and an award-winning former broadcast journalist draw on their experiences to share advice on how to successfully launch a research podcast.


Also from timeshighereducation.com:

An introvert’s guide to networking — from by Yalinu Poya
For academics, networking can greatly enhance your career. But if the very idea fills you with dread, Yalinu Poya offers her advice for putting yourself out there

In academia, meeting the right person can lead to a research collaboration, or it could lead to your work being shared with someone who can use it to make a difference. It could lead to public speaking opportunities or even mentorship. It all goes towards your long-term success.

For some of us, the idea of putting yourself out there in that way – of making an active effort to meet new people – is terrifying.

 

Your AI Writing Partner: The 30-Day Book Framework — from aidisruptor.ai by Alex McFarland and Kamil Banc
How to Turn Your “Someday” Manuscript into a “Shipped” Project Using AI-Powered Prompts

With that out of the way, I prefer Claude.ai for writing. For larger projects like a book, create a Claude Project to keep all context in one place.

  • Copy [the following] prompts into a document
  • Use them in sequence as you write
  • Adjust the word counts and specifics as needed
  • Keep your responses for reference
  • Use the same prompt template for similar sections to maintain consistency

Each prompt builds on the previous one, creating a systematic approach to helping you write your book.


Using NotebookLM to Boost College Reading Comprehension — from michellekassorla.substack.com by Michelle Kassorla and Eugenia Novokshanova
This semester, we are using NotebookLM to help our students comprehend and engage with scholarly texts

We were looking hard for a new tool when Google released NotebookLM. Not only does Google allow unfettered use of this amazing tool, it is also a much better tool for the work we require in our courses. So, this semester, we have scrapped our “old” tools and added NotebookLM as the primary tool for our English Composition II courses (and we hope, fervently, that Google won’t decide to severely limit its free tier before this semester ends!)

If you know next-to-nothing about NotebookLM, that’s OK. What follows is the specific lesson we present to our students. We hope this will help you understand all you need to know about NotebookLM, and how to successfully integrate the tool into your own teaching this semester.


Leadership & Generative AI: Hard-Earned Lessons That Matter — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable Advice for Higher Education Leaders in 2025

AFTER two years of working closely with leadership in multiple institutions, and delivering countless workshops, I’ve seen one thing repeatedly: the biggest challenge isn’t the technology itself, but how we lead through it. Here is some of my best advice to help you navigate generative AI with clarity and confidence:

  1. Break your own AI policies before you implement them.
  2. Fund your failures.
  3. Resist the pilot program. …
  4. Host Anti-Tech Tech Talks
  5. …+ several more tips

While generative AI in higher education obviously involves new technology, it’s much more about adopting a curious and human-centric approach in your institution and communities. It’s about empowering learners in new, human-oriented and innovative ways. It is, in a nutshell, about people adapting to new ways of doing things.



Maria Anderson responded to Clay’s posting with this idea:

Here’s an idea: […] the teacher can use the [most advanced] AI tool to generate a complete solution to “the problem” — whatever that is — and demonstrate how to do that in class. Give all the students access to the document with the results.

And then grade the students on a comprehensive followup activity / presentation of executing that solution (no notes, no more than 10 words on a slide). So the students all have access to the same deep AI result, but have to show they comprehend and can iterate on that result.



Grammarly just made it easier to prove the sources of your text in Google Docs — from zdnet.com by Jack Wallen
If you want to be diligent about proving your sources within Google Documents, Grammarly has a new feature you’ll want to use.

In this age of distrust, misinformation, and skepticism, you may wonder how to demonstrate your sources within a Google Document. Did you type it yourself, copy and paste it from a browser-based source, copy and paste it from an unknown source, or did it come from generative AI?

You may not think this is an important clarification, but if writing is a critical part of your livelihood or life, you will definitely want to demonstrate your sources.

That’s where the new Grammarly feature comes in.

The new feature is called Authorship, and according to Grammarly, “Grammarly Authorship is a set of features that helps users demonstrate their sources of text in a Google doc. When you activate Authorship within Google Docs, it proactively tracks the writing process as you write.”


AI Agents Are Coming to Higher Education — from govtech.com
AI agents are customizable tools with more decision-making power than chatbots. They have the potential to automate more tasks, and some schools have implemented them for administrative and educational purposes.

Custom GPTs are on the rise in education. Google’s version, Gemini Gems, includes a premade version called Learning Coach, and Microsoft announced last week a new agent addition to Copilot featuring use cases at educational institutions.


Generative Artificial Intelligence and Education: A Brief Ethical Reflection on Autonomy — from er.educause.edu by Vicki Strunk and James Willis
Given the widespread impacts of generative AI, looking at this technology through the lens of autonomy can help equip students for the workplaces of the present and of the future, while ensuring academic integrity for both students and instructors.

The principle of autonomy stresses that we should be free agents who can govern ourselves and who are able to make our own choices. This principle applies to AI in higher education because it raises serious questions about how, when, and whether AI should be used in varying contexts. Although we have only begun asking questions related to autonomy and many more remain to be asked, we hope that this serves as a starting place to consider the uses of AI in higher education.

 
© 2025 | Daniel Christian