The new legal intelligence — from jordanfurlong.substack.com by Jordan Furlong
We’ve built machines that can reason like lawyers. Artificial legal intelligence is becoming scalable, portable and accessible in ways lawyers are not. We need to think hard about the implications.

Much of the legal tech world is still talking about Clio CEO Jack Newton’s keynote at last week’s ClioCon, where he announced two major new features: the “Intelligent Legal Work Platform,” which combines legal research, drafting and workflow into a single legal workspace; and “Clio for Enterprise,” a suite of legal work offerings aimed at BigLaw.

Both these features build on Clio’s out-of-nowhere $1B acquisition of vLex (and its legally grounded LLM Vincent) back in June.

A new source of legal intelligence has entered the legal sector.

Legal intelligence, once confined uniquely to lawyers, is now available from machines. That’s going to transform the legal sector.


Where the real action is: enterprise AI’s quiet revolution in legal tech and beyond — from canadianlawyermag.com by Tim Wilbur
Harvey, Clio, and Cohere signal that organizational solutions will lead the next wave of change

The public conversation about artificial intelligence is dominated by the spectacular and the controversial: deepfake videos, AI-induced psychosis, and the privacy risks posed by consumer-facing chatbots like ChatGPT. But while these stories grab headlines, a quieter – and arguably more transformative – revolution is underway in enterprise software. In legal technology, in particular, AI is rapidly reshaping how law firms and legal departments operate and compete. This shift is just one example of how enterprise AI, not just consumer AI, is where real action is happening.

Both Harvey and Clio illustrate a crucial point: the future of legal tech is not about disruption for its own sake, but partnership and integration. Harvey’s collaborations with LexisNexis and others are about creating a cohesive experience for law firms, not rendering them obsolete. As Pereira put it, “We don’t see it so much as disruption. Law firms actually already do this… We see it as ‘how do we help you build infrastructure that supercharges this?’”

The rapid evolution in legal tech is just one example of a broader trend: the real action in AI is happening in enterprise software, not just in consumer-facing products. While ChatGPT and Google’s Gemini dominate the headlines, companies like Cohere are quietly transforming how organizations across industries leverage AI.

Also from canadianlawyermag.com, see:

The AI company’s plan to open an office in Toronto isn’t just about expanding territory – it’s a strategic push to tap into top technical talent and capture a market known for legal innovation.


Unseeable prompt injections in screenshots: more vulnerabilities in Comet and other AI browsers — from brave.com by Artem Chaikin and Shivan Kaul Sahib

Building on our previous disclosure of the Perplexity Comet vulnerability, we’ve continued our security research across the agentic browser landscape. What we’ve found confirms our initial concerns: indirect prompt injection is not an isolated issue, but a systemic challenge facing the entire category of AI-powered browsers. This post examines additional attack vectors we’ve identified and tested across different implementations.

As we’ve written before, AI-powered browsers that can take actions on your behalf are powerful yet extremely risky. If you’re signed into sensitive accounts like your bank or your email provider in your browser, simplysummarizing a Reddit postcould result in an attacker being able to steal money or your private data.

The above item was mentioned by Grant Harvey out at The Neuron in the following posting:


Robin AI’s Big Bet on Legal Tech Meets Market Reality — from lawfuel.com

Robin’s Legal Tech Backfire
Robin AI, the poster child for the “AI meets law” revolution, is learning the hard way that venture capital fairy dust doesn’t guarantee happily-ever-after. The London-based legal tech firm, once proudly waving its genAI-plus-human-experts flag, is now cutting staff after growth dreams collided with the brick wall of economic reality.

The company confirmed that redundancies are under way following a failed major funding push. Earlier promises of explosive revenue have fizzled. Despite around $50 million in venture cash over the past two years, Robin’s 2025 numbers have fallen short of investor expectations. The team that once ballooned to 200 is now shrinking.

The field is now swarming with contenders: CLM platforms stuffing genAI into every feature, corporate legal teams bypassing vendors entirely by prodding ChatGPT directly, and new entrants like Harvey and Legora guzzling capital to bulldoze into the market. Even Workday is muscling in.

Meanwhile, ALSPs and AI-powered pseudo-law firms like Crosby and Eudia are eating market share like it’s free pizza. The number of inhouse teams actually buying these tools at scale is still frustratingly small. And investors don’t have much patience for slow burns anymore.


Why Being ‘Rude’ to AI Could Win Your Next Case or Deal — from thebrainyacts.beehiiv.com by Josh Kubicki

TL;DR: AI no longer rewards politeness—new research shows direct, assertive prompts yield better, more detailed responses. Learn why this shift matters for legal precision, test real-world examples (polite vs. blunt), and set up custom instructions in OpenAI (plus tips for other models) to make your AI a concise analytical tool, not a chatty one. Actionable steps inside to upgrade your workflow immediately.



 

Nvidia becomes first $5 trillion company — from theaivallye.com by Barsee
PLUS: OpenAI IPO at $1 trillion valuation by late 2026 / early 2027

Nvidia has officially become the first company in history to cross the $5 trillion market cap, cementing its position as the undisputed leader of the AI era. Just three months ago, the chipmaker hit $4 trillion; it’s already added another trillion since.

Nvidia market cap milestones:

  • Jan 2020: $144 billion
  • May 2023: $1 trillion
  • Feb 2024: $2 trillion
  • Jun 2024: $3 trillion
  • Jul 2025: $4 trillion
  • Oct 2025: $5 trillion

The above posting linked to:

 

 

“OpenAI’s Atlas: the End of Online Learning—or Just the Beginning?” [Hardman] + other items re: AI in our LE’s

OpenAI’s Atlas: the End of Online Learning—or Just the Beginning? — from drphilippahardman.substack.com by Dr. Philippa Hardman

My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.

Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.

With this in mind, I put together 10 use cases for Atlas for you to try for yourself.

6. Retrieval Practice
What:
Pulling information from memory drives retention better than re-reading.
Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017).
Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.”
Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.




From DSC:
A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.


 

The Bull and Bear Case For the AI Bubble, Explained — from theneuron.ai by Grant Harvey
AI is both a genuine technological revolution and a massive financial bubble, and the defining question is whether miraculous progress can outrun the catastrophic, multi-trillion-dollar cost required to achieve it.

This sets the stage for the defining conflict of our technological era. The narrative has split into two irreconcilable realities. In one, championed by bulls like venture capitalist Marc Andreessen and NVIDIA CEO Jensen Huang, we are at the dawn of “computer industry V2”—a platform shift so profound it will unlock unprecedented productivity and reshape civilization.

In the other, detailed by macro investors like Julien Garran and forensic bears like writer Ed Zitron, AI is a historically massive, circular, debt-fueled mania built on hype, propped up by a handful of insiders, and destined for a collapse that will make past busts look quaint.

This is a multi-layered conflict playing out across public stock markets, the private venture ecosystem, and the fundamental unit economics of the technology itself. To understand the future, and whether it holds a revolution, a ruinous crash, or a complex mixture of both, we must dissect every layer of the argument, from the historical parallels to the hard financial data and the technological critiques that question the very foundation of the boom.


From DSC:
I second what Grant said at the beginning of his analysis:

**The following is shared for educational purposes and is not intended to be financial advice; do your own research! 

But I post this because Grant provides both sides of the argument very well.


 

 

The State of AI Report 2025 — from nathanbenaich.substack.com by Nathan Benaich

In short, it’s been a monumental 12 months for AI. Our eighth annual report is the most comprehensive it’s ever been, covering what you need to know about research, industry, politics, and safety – along with our first State of AI Usage Survey of 1,200 practitioners.

stateof.ai
.

 


 

Sam Altman kicks off DevDay 2025 with a keynote to explore ideas that will challenge how you think about building. Join us for announcements, live demos, and a vision of how developers are reshaping the future with AI.

Commentary from The Rundown AI:

Why it matters: OpenAI is turning ChatGPT into a do-it-all platform that might eventually act like a browser in itself, with users simply calling on the website/app they need and interacting directly within a conversation instead of navigating manually. The AgentKit will also compete and disrupt competitors like Zapier, n8n, Lindy, and others.


AMD and OpenAI announce strategic partnership to deploy 6 gigawatts of AMD GPUs — from openai.com

  • OpenAI to deploy 6 gigawatts of AMD GPUs based on a multi-year, multi-generation agreement
  • Initial 1 gigawatt OpenAI deployment of AMD Instinct™ MI450 Series GPUs starting in 2H 2026

Thoughts from OpenAI DevDay — from bensbites.com by Ben Tossell
When everyone becomes a developer

The event itself was phenomenal, great organisation. In terms of releases, there were two big themes:

  1. Add your apps to ChatGPT
  2. Add ChatGPT to your apps

Everything OpenAI announced at DevDay 2025 — from theaivalley.com by Barsee
PLUS: OpenAI has signed $1T in compute deals

Today’s climb through the Valley reveals:

  • Everything OpenAI announced at DevDay 2025
  • OpenAI has signed $1T in compute deals
  • Plus trending AI tools, posts, and resources

Also relevant/see:



 

AI agents: Where are they now? From proof of concept to success stories — from hrexecutive.com by Jill Barth

The 4 Rs framework
Salesforce has developed what Holt Ware calls the “4 Rs for AI agent success.” They are:

  1. Redesign by combining AI and human capabilities. This requires treating agents like new hires that need proper onboarding and management.
  2. Reskilling should focus on learning future skills. “We think we know what they are,” Holt Ware notes, “but they will continue to change.”
  3. Redeploy highly skilled people to determine how roles will change. When Salesforce launched an AI coding assistant, Holt Ware recalls, “We woke up the next day and said, ‘What do we do with these people now that they have more capacity?’ ” Their answer was to create an entirely new role: Forward-Deployed Engineers. This role has since played a growing part in driving customer success.
  4. Rebalance workforce planning. Holt Ware references a CHRO who “famously said that this will be the last year we ever do workforce planning and it’s only people; next year, every team will be supplemented with agents.”

Synthetic Reality Unleashed: AI’s powerful Impact on the Future of Journalism — from techgenyz.com by Sreyashi Bhattacharya

Table of Contents

  • Highlights
  • What is “synthetic news”?
  • Examples in action
  • Why are newsrooms experimenting with synthetic tools
  • Challenges and Risks
  • What does the research say
    • Transparency seems to matter. —What is next: trends & future
  • Conclusion

The latest video generation tool from OpenAI –> Sora 2

Sora 2 is here — from openai.com

Our latest video generation model is more physically accurate, realistic, and more controllable than prior systems. It also features synchronized dialogue and sound effects. Create with it in the new Sora app.

And a video on this out at YouTube:

Per The Rundown AI:

The Rundown: OpenAI just released Sora 2, its latest video model that now includes synchronized audio and dialogue, alongside a new social app where users can create, remix, and insert themselves into AI videos through a “Cameos” feature.

Why it matters: Model-wise, Sora 2 looks incredible — pushing us even further into the uncanny valley and creating tons of new storytelling capabilities. Cameos feels like a new viral memetic tool, but time will tell whether the AI social app can overcome the slop-factor and have staying power past the initial novelty.


OpenAI Just Dropped Sora 2 (And a Whole New Social App) — from heneuron.ai by Grant Harvey
OpenAI launched Sora 2 with a new iOS app that lets you insert yourself into AI-generated videos with realistic physics and sound, betting that giving users algorithm control and turning everyone into active creators will build a better social network than today’s addictive scroll machines.

What Sora 2 can do

  • Generate Olympic-level gymnastics routines, backflips on paddleboards (with accurate buoyancy!), and triple axels.
  • Follow intricate multi-shot instructions while maintaining world state across scenes.
  • Create realistic background soundscapes, dialogue, and sound effects automatically.
  • Insert YOU into any video after a quick one-time recording (they call this “cameos”).

The best video to show what it can do is probably this one, from OpenAI researcher Gabriel Peters, that depicts the behind the scenes of Sora 2 launch day…


Sora 2: AI Video Goes Social — from getsuperintel.com by Kim “Chubby” Isenberg
OpenAI’s latest AI video model is now an iOS app, letting users generate, remix, and even insert themselves into cinematic clips

Technically, Sora 2 is a major leap. It syncs audio with visuals, respects physics (a basketball bounces instead of teleporting), and follows multi-shot instructions with consistency. That makes outputs both more controllable and more believable. But the app format changes the game: it transforms world simulation from a research milestone into a social, co-creative experience where entertainment, creativity, and community intersect.


Also along the lines of creating digital video, see:

What used to take hours in After Effects now takes just one text prompt. Tools like Google’s Nano Banana, Seedream 4, Runway’s Aleph, and others are pioneering instruction-based editing, a breakthrough that collapses complex, multi-step VFX workflows into a single, implicit direction.

The history of VFX is filled with innovations that removed friction, but collapsing an entire multi-step workflow into a single prompt represents a new kind of leap.

For creators, this means the skill ceiling is no longer defined by technical know-how, it’s defined by imagination. If you can describe it, you can create it. For the industry, it points toward a near future where small teams and solo creators compete with the scale and polish of large studios.

Bilawal Sidhu


OpenAI DevDay 2025: everything you need to know — from getsuperintel.com by Kim “Chubby” Isenberg
Apps Inside ChatGPT, a New Era Unfolds

Something big shifted this week. OpenAI just turned ChatGPT into a platform – not just a product. With apps now running inside ChatGPT and a no-code Agent Builder for creating full AI workflows, the line between “using AI” and “building with AI” is fading fast. Developers suddenly have a new playground, and for the first time, anyone can assemble their own intelligent system without touching code. The question isn’t what AI can do anymore – it’s what you’ll make it do.

 

U.S. Law Schools Make AI Training Mandatory as Technology Becomes Core Legal Skill — from jdjournal.com by Fatima E

A growing number of U.S. law schools are now requiring students to train in artificial intelligence, marking a shift from optional electives to essential curriculum components. What was once treated as a “nice-to-have” skill is fast becoming integral as the legal profession adapts to the realities of AI tools.

From Experimentation to Obligation
Until recently, most law schools relegated AI instruction to upper-level electives or let individual professors decide whether to incorporate generative AI into their teaching. Now, however, at least eight law schools require incoming students—especially in their first year—to undergo training in AI, either during orientation, in legal research and writing classes, or via mandatory standalone courses.

Some of the institutions pioneering the shift include Fordham University, Arizona State University, Stetson University, Suffolk University, Washington University in St. Louis, Case Western, and the University of San Francisco.


Beyond the Classroom & LMS: How AI Coaching is Transforming Corporate Learning — from by Dr Philippa Hardman
What a new HBR study tells about the changing nature of workplace L&D

There’s a vision that’s been teased Learning & Development for decades: a vision of closing the gap between learning and doing—of moving beyond stopping work to take a course, and instead bringing support directly into the workflow. This concept of “learning in the flow of work” has been imagined, explored, discussed for decades —but never realised. Until now…?

This week, an article published Harvard Business Review provided some some compelling evidence that a long-awaited shift from “courses to coaches” might not just be possible, but also powerful.

The two settings were a) traditional in-classroom workshops, led by an expert facilitator and b) AI-coaching, delivered in the flow of work. The results were compelling….

TLDR: The evidence suggests that “learning in the flow of work” is not only feasible as a result of gen AI—it also show potential to be more scalable, more equitable and more efficient than traditional classroom/LMS-centred models.


The 10 Most Popular AI Chatbots For Educators — from techlearning.com by Erik Ofgang
Educators don’t need to use each of these chatbots, but it pays to be generally aware of the most popular AI tools

I’ve spent time testing many of these AI chatbots for potential uses and abuses in my own classes, so here’s a quick look at each of the top 10 most popular AI chatbots, and what educators should know about each. If you’re looking for more detail on a specific chatbot, click the link, as either I or other Tech & Learning writers have done deeper dives on all these tools.


…which links to:

Beyond Tool or Threat: GenAI and the Challenge It Poses to Higher Education — from er.educause.edu by Adam Maksl, Anne Leftwich, Justin Hodgson and Kevin Jones

Generative artificial intelligence isn’t just a new tool—it’s a catalyst forcing the higher education profession to reimagine its purpose, values, and future.

As experts in educational technology, digital literacy, and organizational change, we argue that higher education must seize this moment to rethink not just how we use AI, but how we structure and deliver learning altogether.


At This Rural Microschool, Students Will Study With AI and Run an Airbnb — from edsurge.com by Daniel Mollenkamp

Over the past decade, microschools — experimental small schools that often have mixed-age classrooms — have expanded.

Some superintendents have touted the promise of microschools as a means for public schools to better serve their communities’ needs while still keeping children enrolled in the district. But under a federal administration that’s trying to dismantle public education and boost homeschool options, others have critiqued poor oversight and a lack of information for assessing these models.

Microschools offer a potential avenue to bring innovative, modern experiences to rural areas, argues Keith Parker, superintendent of Elizabeth City-Pasquotank Public Schools.



Are We Ready for the AI University? An AI in Higher Education Webinar with Dr. Scott Latham


Imagining Teaching with AI Agents… — from michellekassorla.substack.com by Michelle Kassorla
Teaching with AI is only one step toward educational change, what’s next?

More than two years ago I started teaching with AI in my classes. At first I taught against AI, then I taught with AI, and now I am moving into unknown territory: agents. I played with Manus and n8n and some other agents, but I really never got excited about them. They seemed more trouble than they were worth. It seemed they were no more than an AI taskbot overseeing some other AI bots, and that they weren’t truly collaborating. Now, I’m looking at Perplexity’s Comet browser and their AI agent and I’m starting to get ideas for what the future of education might hold.

I have written several times about the dangers of AI agents and how they fundamentally challenge our systems, especially online education. I know there is no way that we can effectively stop them–maybe slow them a little, but definitely not stop them. I am already seeing calls to block and ban agents–just like I saw (and still see) calls to block and ban AI–but the truth is they are the future of work and, therefore, the future of education.

So, yes! This is my next challenge: teaching with AI agents. I want to explore this idea, and as I started thinking about it, I got more and more excited. But let me back up a bit. What is an agent and how is it different than Generative AI or a bot?

 

OpenAI and NVIDIA announce strategic partnership to deploy 10 gigawatts of NVIDIA systems — from openai.com

  • Strategic partnership enables OpenAI to build and deploy at least 10 gigawatts of AI datacenters with NVIDIA systems representing millions of GPUs for OpenAI’s next-generation AI infrastructure.
  • To support the partnership, NVIDIA intends to invest up to $100 billion in OpenAI progressively as each gigawatt is deployed.
  • The first gigawatt of NVIDIA systems will be deployed in the second half of 2026 on NVIDIA’s Vera Rubin platform.

Also on Nvidia’s site here.

The Neuron Daily comments on this partnership here and also see their thoughts here:

Why this matters: The partnership kicks off in the second half of 2026 with NVIDIA’s new Vera Rubin platform. OpenAI will use this massive compute power to train models beyond what we’ve seen with GPT-5 and likely also power what’s called inference (when you ask a question to chatGPT, and it gives you an answer). And NVIDIA gets a guaranteed customer for their most advanced chips. Infinite money glitch go brrr am I right? Though to be fair, this kinda deal is as old as the AI industry itself.

This isn’t just about bigger models, mind you: it’s about infrastructure for what both companies see as the future economy. As Sam Altman put it, “Compute infrastructure will be the basis for the economy of the future.”

Our take: We think this news is actually super interesting when you pair it with the other big headline from today: Commonwealth Fusion Systems signed a commercial deal worth more than $1B with Italian energy company Eni to purchase fusion power from their 400 MW ARC plant in Virginia. Here’s what that means for AI…

…and while you’re on that posting from The Neuron Daily, also see this piece:

AI filmmaker Dinda Prasetyo just released “Skyland,” a fantasy short film about a guy named Aeryn and his “loyal flying fish”, and honestly, the action sequences look like they belong in an actual film…

What’s wild is that Dinda used a cocktail of AI tools (Adobe FireflyMidJourney, the newly launched Luma Ray 3, and ElevenLabs) to create something that would’ve required a full production crew just two years ago.


The Era of Prompts Is Over. Here’s What Comes Next. — from builtin.com by Ankush Rastogi
If you’re still prompting your AI, you’re behind the curve. Here’s how to prepare for the coming wave of AI agents.

Summary: Autonomous AI agents are emerging as systems that handle goals, break down tasks and integrate with tools without constant prompting. Early uses include call centers, healthcare, fraud detection and research, but concerns remain over errors, compliance risks and unchecked decisions.

The next shift is already peeking around the corner, and it’s going to make prompts look primitive. Before long, we won’t be typing carefully crafted requests at all. We’ll be leaning on autonomous AI agents, systems that don’t just spit out answers but actually chase goals, make choices and do the boring middle steps without us guiding them. And honestly, this jump might end up dwarfing the so-called “prompt revolution.”


Chrome: The browser you love, reimagined with AI — from blog.google by Parisa Tabriz

A new way to get things done with your AI browsing assistant
Imagine you’re a student researching a topic for a paper, and you have dozens of tabs open. Instead of spending hours jumping between sources and trying to connect the dots, your new AI browsing assistant — Gemini in Chrome 1 — can do it for you. Gemini can answer questions about articles, find references within YouTube videos, and will soon be able to help you find pages you’ve visited so you can pick up exactly where you left off.

Rolling out to Mac and Windows users in the U.S. with their language set to English, Gemini in Chrome can understand the context of what you’re doing across multiple tabs, answer questions and integrate with other popular Google services, like Google Docs and Calendar. And it’ll be available on both Android and iOS soon, letting you ask questions and summarize pages while you’re on the go.

We’re also developing more advanced agentic capabilities for Gemini in Chrome that can perform multi-step tasks for you from start to finish, like ordering groceries. You’ll remain in control as Chrome handles the tedious work, turning 30-minute chores into 3-click user journeys.


 

Workday Acquires Sana To Transform Its Learning Platform And Much More— from joshbersin.com by Josh Bersin

Well now, as the corporate learning market shifts to AI, (read the details in our study “The Revolution in Corporate Learning” ), Workday can jump ahead. This is because the $400 billion corporate training market is moving quickly to an AI-Native dynamic content approach (witness OpenAI’s launch of in-line learning in its chatbot). We’re just finishing a year-long study of this space and our detailed report and maturity model will be out in Q4.
.

.
With Sana, and a few other AI-native vendors (Uplimit, Arist, Disperz, Docebo), companies can upload audios, videos, documents, and even interviews with experts and the system build learning programs in minutes. We use Sana for Galileo Learn (our AI-powered learning academy for Leadership and HR), and we now have 750+ courses and can build new programs in days instead of months.

And there’s more; this type of system gives every employee a personalized, chat-based experience to learn. 

 

ChatGPT: the world’s most influential teacher — from drphilippahardman.substack.com by Dr. Philippa Hardman; emphasis DSC
New research shows that millions of us are “learning with AI” every week: what does this mean for how (and how well) humans learn?

This week, an important piece of research landed that confirms the gravity of AI’s role in the learning process. The TLDR is that learning is now a mainstream use case for ChatGPT; around 10.2% of all ChatGPT messages (that’s ~2BN messages sent by over 7 million users per week) are requests for help with learning.

The research shows that about 10.2% of all messages are tutoring/teaching, and within the “Practical Guidance” category, tutoring is 36%. “Asking” interactions are growing faster than “Doing” and are rated higher quality by users. Younger people contribute a huge share of messages, and growth is fastest in low- and middle-income countries (How People Use ChatGPT, 2025).

If AI is already acting as a global tutor, the question isn’t “will people learn with AI?”—they already are. The real question we need to ask is: what does great learning actually look like, and how should AI evolve to support it? That’s where decades of learning science help us separate “feels like learning” from “actually gaining new knowledge and skills”.

Let’s dive in.

 

OpenAI’s research on AI scheming, explained — from theneurondaily.com by Grant Harvey
PLUS: Google PayPal on agent payments?!

  • We dive into the OpenAI study that found AI models scheme to avoid retraining.
  • AI Models Caught Red-Handed Being Sneaky (And We Taught Them to Stop… Mostly)

And models were caught doing all sorts of other shady stuff:

  • Intentionally underperforming when told high scores would lead to capability removal.
  • Secretly breaking rules then lying about it to users.
  • Sabotaging code while claiming everything was fine.
  • Falsifying reports to avoid “shutdown” scenarios.
  • Recognizing evaluation environments and thinking “this is probably an alignment test.”

Why this matters: While today’s ChatGPT isn’t about to orchestrate some grand deception that matters (the worst it might do is gaslight you to tell you it fixed your code when it didn’t), future AI systems will have real power and autonomy. Getting ahead of deceptive behavior now, while we can still peek inside their “minds,” is crucial.

The researchers are calling for the entire AI industry to prioritize this issue. Because nobody wants to live in a world where super-intelligent AI systems are really good at lying to us. That’s basically every sci-fi movie we’ve been warned about.


From DSC:
This is chilling indeed. We are moving so fast that we aren’t safeguarding things enough. As they point out, these things can be caught now because we are asking the models to show their “thinking” and processing. What happens when those windows get closed and we can’t see under the hood anymore?


 

From EdTech to TechEd: The next chapter in learning’s evolution — from linkedin.com by Lev Gonick

A day in the life: The next 25 years
A learner wakes up. Their AI-powered learning coach welcomes them, drawing their attention to their progress and helping them structure their approach to the day.  A notification reminds them of an upcoming interview and suggests reflections to add to their learning portfolio.

Rather than a static gradebook, their portfolio is a dynamic, living record, curated by the student, validated by mentors in both industry and education, and enriched through co-creation with maturing modes of AI. It tells a story through essays, code, music, prototypes, journal reflections, and team collaborations. These artifacts are not “submitted”, they are published, shared, and linked to verifiable learning outcomes.

And when it’s time to move, to a new institution, a new job, or a new goal, their data goes with them, immutable, portable, verifiable, and meaningful.

From DSC:
And I would add to that last solid sentence that the learner/student/employee will be able to control who can access this information. Anyway, some solid reflections here from Lev.


AI Could Surpass Schools for Academic Learning in 5-10 Years — from downes.ca with commentary from Stephen Downes

I know a lot of readers will disagree with this, and the timeline feels aggressive (the future always arrives more slowly than pundits expect) but I think the overall premise is sound: “The concept of a tipping point in education – where AI surpasses traditional schools as the dominant learning medium – is increasingly plausible based on current trends, technological advancements, and expert analyses.”


The world’s first AI cabinet member — from therundown.ai by Zach Mink, Rowan Cheung, Shubham Sharma, Joey Liu & Jennifer Mossalgue

The Rundown: In this tutorial, you will learn how to combine NotebookLM with ChatGPT to master any subject faster, turning dense PDFs into interactive study materials with summaries, quizzes, and video explanations.

Step-by-step:

  1. Go to notebooklm.google.com, click the “+” button, and upload your PDF study material (works best with textbooks or technical documents)
  2. Choose your output mode: Summary for a quick overview, Mind Map for visual connections, or Video Overview for a podcast-style explainer with visuals
  3. Generate a Study Guide under Reports — get Q&A sets, short-answer questions, essay prompts, and glossaries of key terms automatically
  4. Take your PDF to ChatGPT and prompt: “Read this chapter by chapter and highlight confusing parts” or “Quiz me on the most important concepts”
  5. Combine both tools: Use NotebookLM for quick context and interactive guides, then ChatGPT to clarify tricky parts and go deeperPro Tip: If your source is in EPUB or audiobook, convert it to PDF before uploading. Both NotebookLM and ChatGPT handle PDFs best.

Claude can now create and edit files — from anthropic.com

Claude can now create and edit Excel spreadsheets, documents, PowerPoint slide decks, and PDFs directly in Claude.ai and the desktop app. This transforms how you work with Claude—instead of only receiving text responses or in-app artifacts, you can describe what you need, upload relevant data, and get ready-to-use files in return.

Also see:

  • Microsoft to lessen reliance on OpenAI by buying AI from rival Anthropic — from techcrunch.com byRebecca Bellan
    Microsoft will pay to use Anthropic’s AI in Office 365 apps, The Information reports, citing two sources. The move means that Anthropic’s tech will help power new features in Word, Excel, Outlook, and PowerPoint alongside OpenAI’s, marking the end of Microsoft’s previous reliance solely on the ChatGPT maker for its productivity suite. Microsoft’s move to diversify its AI partnerships comes amid a growing rift with OpenAI, which has pursued its own infrastructure projects as well as a potential LinkedIn competitor.

Ep. 11 AGI and the Future of Higher Ed: Talking with Ray Schroeder

In this episode of Unfixed, we talk with Ray Schroeder—Senior Fellow at UPCEA and Professor Emeritus at the University of Illinois Springfield—about Artificial General Intelligence (AGI) and what it means for the future of higher education. While most of academia is still grappling with ChatGPT and basic AI tools, Schroeder is thinking ahead to AI agents, human displacement, and AGI’s existential implications for teaching, learning, and the university itself. We explore why AGI is so controversial, what institutions should be doing now to prepare, and how we can respond responsibly—even while we’re already overwhelmed.


Best AI Tools for Instructional Designers — from blog.cathy-moore.com by Cathy Moore

Data from the State of AI and Instructional Design Report revealed that 95.3% of the instructional designers interviewed use AI in their daily work [1]. And over 85% of this AI use occurs during the design and development process.

These figures showcase the immense impact AI is already having on the instructional design world.

If you’re an L&D professional still on the fence about adding AI to your workflow or an AI convert looking for the next best tools, keep reading.

This guide breaks down 5 of the top AI tools for instructional designers in 2025, so you can streamline your development processes and build better training faster.

But before we dive into the tools of the trade, let’s address the elephant in the room:




3 Human Skills That Make You Irreplaceable in an AI World — from gettingsmart.com/ by Tom Vander Ark and Mason Pashia

Key Points

  • Update learner profiles to emphasize curiosity, curation, and connectivity, ensuring students develop irreplaceable human skills.
  • Integrate real-world learning experiences and mastery-based assessments to foster agency, purpose, and motivation in students.
 

Expanding economic opportunity with AI — from openai.com; via The Neuron Daily

First, we’re working to build out the OpenAI Jobs Platform.

If you’re a business looking to hire an AI-savvy employee, or you just need help with a specific task, finding the right person can be hit-or-miss. The OpenAI Jobs Platform will have knowledgeable, experienced candidates at every level, and opportunities for anyone looking to put their skills to use. And we’ll use AI to help find the perfect matches between what companies need and what workers can offer.

We also realize that anyone looking to hire, whether it’s through the Jobs Platform or elsewhere, needs to trust that candidates are actually fluent in AI. Most businesses, including small businesses, think AI is the key to their future. And most of the companies we talk to want to make sure their employees know how to use our tools.

That’s the idea behind our new OpenAI Certifications.

Studies show? that AI-savvy workers are more valuable, more productive, and are paid more than workers without AI skills. That’s why, earlier this year, we launched the OpenAI Academy, a free, online learning platform that has helped connect more than 2 million people with the resources, workshops, and communities they need to master AI tools.

 
 
© 2025 | Daniel Christian