emerging technologies

“ElevenLabs just launched a voice marketplace” + [GIFTED ARTICLE] “How people really use ChatGPT” + several other items re: AI in general

On 11/13/2025, in 21st century, 24x7x365 access, A/V -- audio/visual, Artificial Intelligence/Agents/LLMs/and Related, bots, computer science, content development, aggregation, repositories, corporate / business world, creativity, digital audio, emerging technologies, Emotion, engagement / engaging students, experimentation, global / globalization, history, human-computer interaction (HCI), innovation, media/film, platforms, play, productivity / tips and tricks, programming, society, story, storytelling, the downsides of how people use tech, tools, trends, United States, vendors, by Daniel Christian

ElevenLabs just launched a voice marketplace — from elevenlabs.io; via theaivalley.com

Via the AI Valley:

Why does it matter?
AI voice cloning has already flooded the internet with unauthorized imitations, blurring legal and ethical lines. By offering a dynamic, rights-secured platform, ElevenLabs aims to legitimize the booming AI voice industry and enable transparent, collaborative commercialization of iconic IP.
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[GIFTED ARTICLE] How people really use ChatGPT, according to 47,000 conversations shared online — from by Gerrit De Vynck and Jeremy B. Merrill
What do people ask the popular chatbot? We analyzed thousands of chats to identify common topics discussed by users and patterns in ChatGPT’s responses.

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Data released by OpenAI in September from an internal study of queries sent to ChatGPT showed that most are for personal use, not work.

Emotional conversations were also common in the conversations analyzed by The Post, and users often shared highly personal details about their lives. In some chats, the AI tool could be seen adapting to match a user’s viewpoint, creating a kind of personalized echo chamber in which ChatGPT endorsed falsehoods and conspiracy theories.

Lee Rainie, director of the Imagining the Digital Future Center at Elon University, said his own research has suggested ChatGPT’s design encourages people to form emotional attachments with the chatbot. “The optimization and incentives towards intimacy are very clear,” he said. “ChatGPT is trained to further or deepen the relationship.”

Per The Rundown: OpenAI just shared its view on AI progress, predicting systems will soon become smart enough to make discoveries and calling for global coordination on safety, oversight, and resilience as the technology nears superintelligent territory.

The details:

OpenAI said current AI systems already outperform top humans in complex intellectual tasks and are “80% of the way to an AI researcher.”
The company expects AI will make small scientific discoveries by 2026 and more significant breakthroughs by 2028, as intelligence costs fall 40x per year.
For superintelligent AI, OAI said work with governments and safety agencies will be essential to mitigate risks like bioterrorism or runaway self-improvement.
It also called for safety standards among top labs, a resilience ecosystem like cybersecurity, and ongoing tracking of AI’s real impact to inform public policy.

Why it matters: While the timeline remains unclear, OAI’s message shows that the world should start bracing for superintelligent AI with coordinated safety. The company is betting that collective safeguards will be the only way to manage risk from the next era of intelligence, which may diffuse in ways humanity has never seen before.

Which linked to:

AI progress and recommendations — from openai.com
AI is unlocking new knowledge and capabilities. Our responsibility is to guide that power toward broad, lasting benefit.

From DSC:
I hate to say this, but it seems like there is growing concern amongst those who have pushed very hard to release as much AI as possible — they are NOW worried. They NOW step back and see that there are many reasons to worry about how these technologies can be negatively used.

Where was this level of concern before (while they were racing ahead at 180 mph)? Surely, numerous and knowledgeable people inside those organizations warned them about the destructive/downside of these technologies. But their warnings were pretty much blown off (at least from my limited perspective).

The state of AI in 2025: Agents, innovation, and transformation — from mckinsey.com

Key findings

Most organizations are still in the experimentation or piloting phase: Nearly two-thirds of respondents say their organizations have not yet begun scaling AI across the enterprise.
High curiosity in AI agents: Sixty-two percent of survey respondents say their organizations are at least experimenting with AI agents.
Positive leading indicators on impact of AI: Respondents report use-case-level cost and revenue benefits, and 64 percent say that AI is enabling their innovation. However, just 39 percent report EBIT impact at the enterprise level.
High performers use AI to drive growth, innovation, and cost: Eighty percent of respondents say their companies set efficiency as an objective of their AI initiatives, but the companies seeing the most value from AI often set growth or innovation as additional objectives.
Redesigning workflows is a key success factor: Half of those AI high performers intend to use AI to transform their businesses, and most are redesigning workflows.
Differing perspectives on employment impact: Respondents vary in their expectations of AI’s impact on the overall workforce size of their organizations in the coming year: 32 percent expect decreases, 43 percent no change, and 13 percent increases.

Marble: A Multimodal World Model — from worldlabs.ai

Spatial intelligence is the next frontier in AI, demanding powerful world models to realize its full potential. World models should reconstruct, generate, and simulate 3D worlds; and allow both humans and agents to interact with them. Spatially intelligent world models will transform a wide variety of industries over the coming years.

Two months ago we shared a preview of Marble, our World Model that creates 3D worlds from image or text prompts. Since then, Marble has been available to an early set of beta users to create 3D worlds for themselves.

Today we are making Marble, a first-in-class generative multimodal world model, generally available for anyone to use. We have also drastically expanded Marble’s capabilities, and are excited to highlight them here:

How is AI impacting the learning ecosystems out there (esp. L&D)? Check these postings out.

On 11/13/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, assessment, bots, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, Europe, faculty/staff, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, Microsoft, online learning, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, tools, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

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Gen AI Is Going Mainstream: Here’s What’s Coming Next — from joshbersin.com by Josh Bersin

I just completed nearly 60,000 miles of travel across Europe, Asia, and the Middle East meeting with hundred of companies to discuss their AI strategies. While every company’s maturity is different, one thing is clear: AI as a business tool has arrived: it’s real and the use-cases are growing.

A new survey by Wharton shows that 46% of business leaders use Gen AI daily and 80% use it weekly. And among these users, 72% are measuring ROI and 74% report a positive return. HR, by the way, is the #3 department in use cases, only slightly behind IT and Finance.

What are companies getting out of all this? Productivity. The #1 use case, by far, is what we call “stage 1” usage – individual productivity.

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From DSC:
Josh writes: “Many of our large clients are now implementing AI-native learning systems and seeing 30-40% reduction in staff with vast improvements in workforce enablement.”

While I get the appeal (and ROI) from management’s and shareholders’ perspective, this represents a growing concern for employment and people’s ability to earn a living.

And while I highly respect Josh and his work through the years, I disagree that we’re over the problems with AI and how people are using it:

Two years ago the NYT was trying to frighten us with stories of AI acting as a romance partner. Well those stories are over, and thanks to a $Trillion (literally) of capital investment in infrastructure, engineering, and power plants, this stuff is reasonably safe.

Those stories are just beginning…they’re not close to being over.

“… imagine a world where there’s no separation between learning and assessment…” — from aiedusimplified.substack.com by Lance Eaton, Ph.D. and Tawnya Means
An interview with Tawnya Means

So let’s imagine a world where there’s no separation between learning and assessment: it’s ongoing. There’s always assessment, always learning, and they’re tied together. Then we can ask: what is the role of the human in that world? What is it that AI can’t do?
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Imagine something like that in higher ed. There could be tutoring or skill-based work happening outside of class, and then relationship-based work happening inside of class, whether online, in person, or some hybrid mix.

The aspects of learning that don’t require relational context could be handled by AI, while the human parts remain intact. For example, I teach strategy and strategic management. I teach people how to talk with one another about the operation and function of a business. I can help students learn to be open to new ideas, recognize when someone pushes back out of fear of losing power, or draw from my own experience in leading a business and making future-oriented decisions.

But the technical parts such as the frameworks like SWOT analysis, the mechanics of comparing alternative viewpoints in a boardroom—those could be managed through simulations or reports that receive immediate feedback from AI. The relational aspects, the human mentoring, would still happen with me as their instructor.

Part 2 of their interview is here:

“They’re not necessarily trying to cheat; they’re just being efficient”

A New AI Career Ladder — from ssir.org (Stanford Social Innovation Review) by Bruno V. Manno; via Matt Tower
The changing nature of jobs means workers need new education and training infrastructure to match.

AI has cannibalized the routine, low-risk work tasks that used to teach newcomers how to operate in complex organizations. Without those task rungs, the climb up the opportunity ladder into better employment options becomes steeper—and for many, impossible. This is not a temporary glitch. AI is reorganizing work, reshaping what knowledge and skills matter, and redefining how people are expected to acquire them.

The consequences ripple from individual career starts to the broader American promise of economic and social mobility, which includes both financial wealth and social wealth that comes from the networks and relationships we build. Yet the same technology that complicates the first job can help us reinvent how experience is earned, validated, and scaled. If we use AI to widen—not narrow—access to education, training, and proof of knowledge and skill, we can build a stronger career ladder to the middle class and beyond. A key part of doing this is a redesign of education, training, and hiring infrastructure.

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What’s needed is a redesigned model that treats work as a primary venue for learning, validates capability with evidence, and helps people keep climbing after their first job. Here are ten design principles for a reinvented education and training infrastructure for the AI era.

Create hybrid institutions that erase boundaries. …
Make work-based learning the default, not the exception. …
Create skill adjacencies to speed transitions. …
Place performance-based hiring at the core. …
Ongoing supports and post-placement mobility. …
Portable, machine-readable credentials with proof attached. …
…plus several more…

China just broke a world record with 16,000 AI-powered drones flying perfectly together, controlled by a smart Al system.

On 11/06/2025, in A/V -- audio/visual, Artificial Intelligence/Agents/LLMs/and Related, Asia, creativity, emerging technologies, engagement / engaging students, engineering, ideas, robotics, science, by Daniel Christian

?BREAKING: China just broke a world record with 16,000 AI-powered drones flying perfectly together, controlled by a smart Al system.

This happened at Liuyang, Hunan, famously known as the "Home of Fireworks"
pic.twitter.com/muaIaD3wiO

— Future Stacked (@FutureStacked) November 4, 2025

The problem with just handing over an army of agents to junior consultants + other items re: AI in general

On 11/05/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, changing business models, collaboration, emerging technologies, experimentation, leadership, strategy, the downsides of how people use tech, tools, United States, vendors, workplace, by Daniel Christian

KPMG wants junior consultants to ditch the grunt work and hand it over to teams of AI agents — from businessinsider.com by Polly Thompson

The Big Four consulting and accounting firm is training its junior consultants to manage teams of AI agents — digital assistants capable of completing tasks without human input.

“We want juniors to become managers of agents,” Niale Cleobury, KPMG’s global AI workforce lead, told Business Insider in an interview.

KPMG plans to give new consulting recruits access to a catalog of AI agents capable of creating presentation slides, analyzing data, and conducting in-depth research, Cleobury said.

The goal is for these agents to perform much of the analytical and administrative work once assigned to junior consultants, allowing them to become more involved in strategic decisions.

From DSC:
For a junior staff member to provide quality assurance in working with agents, an employee must know what they’re talking about in the first place. They must have expertise and relevant knowledge. Otherwise, how will they spot the hallucinations?

So the question is, how can businesses build such expertise in junior staff members while they are delegating things to an army of agents? This question applies to the next posting below as well. Having agents report to you is all well and good — IF you know when the agents are producing helpful/accurate information and when they got things all wrong.

This Is the Next Vital Job Skill in the AI Economy — from builtin.com by Saurabh Sharma
The future of tech work belongs to AI managers.

Summary: A fundamental shift is making knowledge workers “AI managers.” The most valuable employees will direct intelligent AI agents, which requires new competencies: delegation, quality assurance and workflow orchestration across multiple agents. Companies must bridge the training gap to enable this move from simple software use to strategic collaboration with intelligent, yet imperfect, systems.

The shift is happening subtly, but it’s happening. Workers are learning to prompt agents, navigate AI capabilities, understand failure modes and hand off complex tasks to AI. And if they haven’t started yet, they probably will: A new study from IDC and Salesforce found that 72 percent of CEOs think most employees will have an AI agent reporting to them within five years. This isn’t about using a new kind of software tool — it’s about directing intelligent systems that can reason, search, analyze and create.

Soon, the most valuable employees won’t just know how to use AI; they’ll know how to manage it. And that requires a fundamentally different skill set than anything we’ve taught in the workplace before.

AI agents failed 97% of freelance tasks; here’s why… — from theneurondaily.com by Grant Harvey

AI Agents Can’t Actually Do Your Job (Yet)—New Benchmark Reveals The Gap

DEEP DIVE: AI can make you faster at your job, but can only do 2-3% of jobs by itself.

The hype: AI agents will automate entire workflows! Replace freelancers! Handle complex tasks end-to-end!

The reality: a measly 2-3% completion rate.

See, Scale AI and CAIS just released the Remote Labor Index (paper), a benchmark where AI agents attempted real freelance tasks. The best-performing model earned just $1,810 out of $143,991 in available work, and yes, finishing only 2-3% of jobs.

“This isn’t a cheating crisis. It’s an identify crisis [for higher education].” + numerous other items re: AI in our LE’s

On 11/05/2025, in active learning, apprenticeships, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, colleges, community colleges, content development, aggregation, repositories, dangers of the status quo, education technology, emerging technologies, face-to-face, faculty/staff, future of higher education, game-changing environment, higher education, ideas, innovation, instructional design, intelligent systems, learning, learning ecosystem, Learning Experience Design, liberal arts, pedagogy, reinvent, society, staying relevant, student-related, surviving, teaching & learning, trends, UK, United States, universities, vision/possibilities, by Daniel Christian

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…the above posting links to:

Higher Ed Is Sleepwalking Toward Obsolescence— And AI Won’t Be the Cause, Just the Accelerant — from substack.com by Steven Mintz
AI Has Exposed Higher Ed’s Hollow Core — The University Must Reinvent Itself or Fade

It begins with a basic reversal of mindset: Stop treating AI as a threat to be policed. Start treating it as the accelerant that finally forces us to build the education we should have created decades ago.

A serious institutional response would demand — at minimum — six structural commitments:

Make high-intensity human learning the norm. …
Put active learning at the center, not the margins. …
Replace content transmission with a focus on process. …
Mainstream high-impact practices — stop hoarding them for honors students. …
Redesign assessment to make learning undeniable. …

And above all: Instructional design can no longer be a private hobby.

Teaching with AI: From Prohibition to Partnership for Critical Thinking — from facultyfocus.com by Michael Kiener, PhD, CRC

How to Integrate AI Developmentally into Your Courses

Lower-Level Courses: Focus on building foundational skills, which includes guided instruction on how to use AI responsibly. This moves the strategy beyond mere prohibition.
Mid-Level Courses: Use AI as a scaffold where faculty provide specific guidelines on when and how to use the tool, preparing students for greater independence.
Upper-Level/Graduate Courses: Empower students to evaluate AI’s role in their learning. This enables them to become self-regulated learners who make informed decisions about their tools.
Balanced Approach: Make decisions about AI use based on the content being learned and students’ developmental needs.

Now that you have a framework for how to conceptualize including AI into your courses here are a few ideas on scaffolding AI to allow students to practice using technology and develop cognitive skills.

80 per cent of young people in the UK are using AI for their schoolwork — from aipioneers.org by Graham Attwell

What was encouraging, though, is that students aren’t just passively accepting this new reality. They are actively asking for help. Almost half want their teachers to help them figure out what AI-generated content is trustworthy, and over half want clearer guidelines on when it’s appropriate to use AI in their work. This isn’t a story about students trying to cheat the system; it’s a story about a generation grappling with a powerful new technology and looking to their educators for guidance. It echoes a sentiment I heard at the recent AI Pioneers’ Conference – the issue of AI in education is fundamentally pedagogical and ethical, not just technological.

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.
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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?’”
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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:

Harvey’s $5 billion bet: Why the hottest company in legal tech is eyeing Canada
Co-founder Gabe Pereyra says their new Toronto office will have both tech expertise and customer support

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:

AI browser risks and the “AI trust tax” you’re already paying — from theneurondaily.com by Grant Harvey
PLUS: OpenAI’s new music maker + China’s 90% power?cut AI server.

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.

“…a new operating system for L&D in the age of AI?” [Hardman] + other items re: AI in our learning ecosystems

On 10/30/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, higher education, human-computer interaction (HCI), India, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, liberal arts, training / L&D, by Daniel Christian

Custom AI Development: Evolving from Static AI Systems to Dynamic Learning Agents in 2025 — community.nasscom.in

This blog explores how custom AI development accelerates the evolution from static AI to dynamic learning agents and why this transformation is critical for driving innovation, efficiency, and competitive advantage.
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Dynamic Learning Agents: The Next Generation
Dynamic learning agents, sometimes referred to as adaptive or agentic AI, represent a leap forward. They combine continuous learning, autonomous action, and context-aware adaptability.

Custom AI development plays a crucial role here: it ensures that these agents are designed specifically for an enterprise’s unique needs rather than relying on generic, one-size-fits-all AI platforms. Tailored dynamic agents can:

Continuously learn from incoming data streams
Make autonomous, goal-directed decisions aligned with business objectives
Adapt behavior in real time based on context and feedback
Collaborate with other AI agents and human teams to solve complex challenges

The result is an AI ecosystem that evolves with the business, providing sustained competitive advantage.

Also from community.nasscom.in, see:

Building AI Agents with Multimodal Models: From Perception to Action

Perception: The Foundation of Intelligent Agents
Perception is the first step in building AI agents. It involves capturing and interpreting data from multiple modalities, including text, images, audio, and structured inputs. A multimodal AI agent relies on this comprehensive understanding to make informed decisions.

For example, in healthcare, an AI agent may process electronic health records (text), MRI scans (vision), and patient audio consultations (speech) to build a complete understanding of a patient’s condition. Similarly, in retail, AI agents can analyze purchase histories (structured data), product images (vision), and customer reviews (text) to inform recommendations and marketing strategies.

Effective perception ensures that AI agents have contextual awareness, which is essential for accurate reasoning and appropriate action.

From 70-20-10 to 90-10: a new operating system for L&D in the age of AI? — from linkedin.com by Dr. Philippa Hardman

Also from Philippa, see:

Defining & Navigating the Jagged Frontier in Instructional Design (October, 2025)
What we know about where AI helps (and where it hinders) Instructional Design, and how to manage it

Your New ChatGPT Guide — from wondertools.substack.com by Jeremy Caplan and The PyCoach
25 AI Tips & Tricks from a guest expert

ChatGPT can make you more productive or dumber. An MIT study found that while AI can significantly boost productivity, it may also weaken your critical thinking. Use it as an assistant, not a substitute for your brain.
If you’re a student, use study mode in ChatGPT, Gemini, or Claude. When this feature is enabled, the chatbots will guide you through problems rather than just giving full answers, so you’ll be doing the critical thinking.
ChatGPT and other chatbots can confidently make stuff up (aka AI hallucinations). If you suspect something isn’t right, double-check its answers.
NotebookLM hallucinates less than most AI tools, but it requires you to upload sources (PDFs, audio, video) and won’t answer questions beyond those materials. That said, it’s great for students and anyone with materials to upload.
Probably the most underrated AI feature is deep research. It automates web searching for you and returns a fully cited report with minimal hallucinations in five to 30 minutes. It’s available in ChatGPT, Perplexity, and Gemini, so give it a try.

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

On 10/28/2025, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, assistive technologies, change, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, internet, IT in HE, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, learning theories, liberal arts, library / librarians, lifelong learning, memory, online learning, online media, online tutoring, Open AI, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, reading, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vendors, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

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.
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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.

“How do we optimize an AI to support learning?” [Downes] + several other items re: AI in our LE’s

On 10/23/2025, in 21st century, 24x7x365 access, accessibility / UDL, Artificial Intelligence/Agents/LLMs/and Related, bots, Canada, colleges, communications, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, languages and translation, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, neurodivergent/special needs, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, trends, United States, universities, writing, by Daniel Christian

There is no God Tier video model — from downes.ca by Stephen Downes

From DSC:
Stephen has some solid reflections and asks some excellent questions in this posting, including:

The question is: how do we optimize an AI to support learning? Will one model be enough? Or do we need different models for different learners in different scenarios?

A More Human University: The Role of AI in Learning — from er.educause.edu by Robert Placido
Far from heralding the collapse of higher education, artificial intelligence offers a transformative opportunity to scale meaningful, individualized learning experiences across diverse classrooms.

The narrative surrounding artificial intelligence (AI) in higher education is often grim. We hear dire predictions of an “impending collapse,” fueled by fears of rampant cheating, the erosion of critical thinking, and the obsolescence of the human educator.Footnote1 This dystopian view, however, is a failure of imagination. It mistakes the death rattle of an outdated pedagogical model for the death of learning itself. The truth is far more hopeful: AI is not an asteroid coming for higher education. It is a catalyst that can finally empower us to solve our oldest, most intractable problem: the inability to scale deep, engaged, and truly personalized learning.

Claude for Life Sciences — from anthropic.com

Increasing the rate of scientific progress is a core part of Anthropic’s public benefit mission.

We are focused on building the tools to allow researchers to make new discoveries – and eventually, to allow AI models to make these discoveries autonomously.

Until recently, scientists typically used Claude for individual tasks, like writing code for statistical analysis or summarizing papers. Pharmaceutical companies and others in industry also use it for tasks across the rest of their business, like sales, to fund new research. Now, our goal is to make Claude capable of supporting the entire process, from early discovery through to translation and commercialization.

To do this, we’re rolling out several improvements that aim to make Claude a better partner for those who work in the life sciences, including researchers, clinical coordinators, and regulatory affairs managers.

AI as an access tool for neurodiverse and international staff — from timeshighereducation.com by Vanessa Mar-Molinero
Used transparently and ethically, GenAI can level the playing field and lower the cognitive load of repetitive tasks for admin staff, student support and teachers

Where AI helps without cutting academic corners
When framed as accessibility and quality enhancement, AI can support staff to complete standard tasks with less friction. However, while it supports clarity, consistency and inclusion, generative AI (GenAI) does not replace disciplinary expertise, ethical judgement or the teacher–student relationship. These are ways it can be put to effective use:

Drafting and tone calibration: …
Language scaffolding: …
Structure and templates: ..
Summarise and prioritise: …
Accessibility by default: …
Idea generation for pedagogy: …
Translation and cultural mediation: …

Beyond learning design: supporting pedagogical innovation in response to AI — from timeshighereducation.com by Charlotte von Essen
To avoid an unwinnable game of catch-up with technology, universities must rethink pedagogical improvement that goes beyond scaling online learning

The Sleep of Liberal Arts Produces AI — from aiedusimplified.substack.com by Lance Eaton, Ph.D.
A keynote at the AI and the Liberal Arts Symposium Conference

This past weekend, I had the honor to be the keynote speaker at a really fantstistic conferece, AI and the Liberal Arts Symposium at Connecticut College. I had shared a bit about this before with my interview with Lori Looney. It was an incredible conference, thoughtfully composed with a lot of things to chew on and think about.

It was also an entirely brand new talk in a slightly different context from many of my other talks and workshops. It was something I had to build entirely from the ground up. It reminded me in some ways of last year’s “What If GenAI Is a Nothingburger”.

It was a real challenge and one I’ve been working on and off for months, trying to figure out the right balance. It’s a work I feel proud of because of the balancing act I try to navigate. So, as always, it’s here for others to read and engage with. And, of course, here is the slide deck as well (with CC license).

The Most Innovative Law Schools (2025) — from abovethelaw.com by Staci Zaretsky
Forget dusty casebooks — today’s leaders in legal education are using AI, design thinking, and real-world labs to reinvent how law is taught.

“[F]rom AI labs and interdisciplinary centers to data-driven reform and bold new approaches to design and client service,” according to National Jurist’s preLaw Magazine, these are the law schools that “exemplify innovation in action.”

North Carolina Central University School of Law
Suffolk University Law School
UC Berkeley School of Law
Nova Southeastern University Shepard Broad College of Law
Northeastern University School of Law
Maurice A. Deane School of Law at Hofstra University
Seattle University School of Law
Case Western Reserve University School of Law
University of Miami School of Law
Benjamin N. Cardozo School of Law at Yeshiva University
Vanderbilt University Law School
Southwestern Law School

Click here to read short summaries of why each school made this year’s list of top innovators.

Clio’s Metamorphosis: From Practice Management To A Comprehensive AI And Law Practice Provider — from abovethelaw.com by Stephen Embry
Clio is no longer a practice management company. It’s much more of a comprehensive provider of all needs of its customers big and small.

Newton delivered what may have been the most consequential keynote in the company’s history and one that signals a shift by Clio from a traditional practice management provider to a comprehensive platform that essentially does everything for the business and practice of law.
…
Clio also earlier this year acquired vLex, the heavy-duty AI legal research player. The acquisition is pending regulatory approval. It is the vLex acquisition that is powering the Clio transformation that Newton described in his keynote.

vLex has a huge amount of legal data in its wheelhouse to power sophisticated legal AI research. On top of this data, vLex developed Vincent, a powerful AI tool to work with this data and enable all sorts of actions and work.

This means a couple of things. First, by acquiring vLex, Clio can now offer its customers AI legal research tools. Clio customers will no longer have to go one place for its practice management needs and a second place for its substantive legal work, like research. It makes what Clio can provide much more comprehensive and all inclusive.

‘Adventures In Legal Tech’: How AI Is Changing Law Firms — from abovethelaw.com
Ernie the Attorney shares his legal tech takes.

Artificial intelligence will give solos and small firms “a huge advantage,” according to one legal tech consultant.

In this episode of “Adventures in Legal Tech,” host Jared Correia speaks with Ernie Svenson — aka “Ernie the Attorney” — about the psychology behind resistance to change, how law firms are positioning their AI use, the power of technology for business development, and more.

Legal software: how to look for and compare AI in legal technology — from legal.thomsonreuters.com by Chris O’Leary

Highlights

Legal ops experts can categorize legal AI platforms and software by the ability to streamline key tasks such as legal research, document processing or analysis, and drafting.
The trustworthiness and accuracy of AI hinge on the quality of its underlying data; solutions like CoCounsel Legal are grounded in authoritative, expert-verified content from Westlaw and Practical Law, unlike providers that may rely on siloed or less reliable databases.
When evaluating legal software, firms should use a framework that assesses critical factors such as integration with existing tech stacks, security, scalability, user adoption, and vendor reputation.

ASU Law appoints a director of AI and Legal Tech Studio, advancing its initiative to reimagine legal education — from law.asu.edu

The Sandra Day O’Connor College of Law at Arizona State University appointed Sean Harrington as director of the newly established AI and Legal Tech Studio, a key milestone in ASU Law’s bold initiative to reimagine legal education for the artificial intelligence era. ASU, ranked No. 1 in innovation for the 11th consecutive year, drives AI solutions that enhance teaching, enrich student training and facilitate digital transformation.

The American Legal Technology Awards Name 2025 Winners — from natlawreview.com by Tom Martin

The sixth annual American Legal Technology Awards were presented on Wednesday, October 15th, at Suffolk University Law School (Boston), recognizing winners across ten categories. There were 211 nominees who were evaluated by 27 judges.

The honorees on the night included:

2. Concern and excitement about AI — from pewresearch.org by Jacob Poushter,Moira Faganand Manolo Corichi

Key findings

A median of 34% of adults across 25 countries are more concerned than excited about the increased use of artificial intelligence in daily life. A median of 42% are equally concerned and excited, and 16% are more excited than concerned.
Older adults, women, people with less education and those who use the internet less often are particularly likely to be more concerned than excited.

Also relevant here:

The U.S. Public Wants Regulation (or Prohibition) of Expert-Level and Superhuman AI — from futureoflife.org
Three?quarters of U.S. adults want strong regulations on AI development, preferring oversight akin to pharmaceuticals rather than industry “self?regulation.”

AI Video Wars include Veo 3.1, Sora 2, Ray3, Kling 2.5 + Wan 2.5 — from heatherbcooper.substack.com by Heather Cooper
House of David Season 2 is here!

In today’s edition:

Veo 3.1 brings richer audio and object-level editing to Google Flow
Sora 2 is here with Cameo self-insertion and collaborative Remix features
Ray3 brings world-first reasoning and HDR to video generation
Kling 2.5 Turbo delivers faster, cheaper, more consistent results
WAN 2.5 revolutionizes talking head creation with perfect audio sync
House of David Season 2 Trailer
HeyGen Agent, Hailuo Agent, Topaz Astra, and Lovable Cloud updates
Image & Video Prompts

From DSC:
By the way, the House of David (which Heather referred to) is very well done! I enjoyed watching Season 1. Like The Chosen, it brings the Bible to life in excellent, impactful ways! Both series convey the context and cultural tensions at the time. Both series are an answer to prayer for me and many others — as they are professionally-done. Both series match anything that comes out of Hollywood in terms of the acting, script writing, music, the sets, etc. Both are very well done.
.

An item re: Sora:

Association of Talent Agents, United Talent Agency, Creative Artists Agency also Join to Protect Performers. — from sagaftra.org

Other items re: Open AI’s new Atlas browser:

Introducing ChatGPT Atlas — from openai.com
The browser with ChatGPT built in.

[On 10/21/25] we’re introducing ChatGPT Atlas, a new web browser built with ChatGPT at its core.

AI gives us a rare moment to rethink what it means to use the web. Last year, we added search in ChatGPT so you could instantly find timely information from across the internet—and it quickly became one of our most-used features. But your browser is where all of your work, tools, and context come together. A browser built with ChatGPT takes us closer to a true super-assistant that understands your world and helps you achieve your goals.

With Atlas, ChatGPT can come with you anywhere across the web—helping you in the window right where you are, understanding what you’re trying to do, and completing tasks for you, all without copying and pasting or leaving the page. Your ChatGPT memory is built in, so conversations can draw on past chats and details to help you get new things done.

ChatGPT Atlas: the AI browser test — from getsuperintel.com by Kim “Chubby” Isenberg
Chat GPT Atlas aims to transform web browsing into a conversational, AI-native experience, but early reviews are mixed

OpenAI’s new ChatGPT Atlas promises to merge web browsing, search, and automation into a single interface — an “AI-native browser” meant to make the web conversational. After testing it myself, though, I’m still trying to see the real breakthrough. It feels familiar: summaries, follow-ups, and even the Agent’s task handling all mirror what I already do inside ChatGPT.

OpenAI’s new Atlas browser remembers everything — from theneurondaily.com by Grant Harvey
PLUS: Our AIs are getting brain rot?!

Here’s how it works: Atlas can see what you’re looking at on any webpage and instantly help without you needing to copy/paste or switch tabs. Researching hotels? Ask ChatGPT to compare prices right there. Reading a dense article? Get a summary on the spot. The AI lives in the browser itself.

OpenAI’s new product — from bensbites.com

The latest entry in AI browsers is Atlas – A new browser from OpenAI. Atlas would feel similar to Dia or Comet if you’ve used them. It has an “Ask ChatGPT” sidebar that has the context of your page, and choose “Agent” to work on that tab. Right now, Agent is limited to a single tab, and it is way too slow to delegate anything for real to it. Click accuracy for Agent is alright on normal web pages, but it will definitely trip up if you ask it to use something like Google Sheets.

One ambient feature that I think many people will like is “select to rewrite” – You can select any text in Atlas, hover/click on the blue dot in the top right corner to rewrite it using AI.

Your AI Resume Hacks Probably Won’t Fool Hiring Algorithms — from builtin.com by Jeff Rumage
Recruiters say those viral hidden prompt for resumes don’t work — and might cost you interviews.

Summary: Job seekers are using “prompt hacking” — embedding hidden AI commands in white font on resumes — to try to trick applicant tracking systems. While some report success, recruiters warn the tactic could backfire and eliminate the candidate from consideration.

The Job Market Might Be a Mess, But Don’t Blame AI Just Yet — from builtin.com by Matthew Urwin
A new study by Yale University and the Brookings Institution says the panic around artificial intelligence stealing jobs is overblown. But that might not be the case for long.

Summary: A Yale and Brookings study finds generative AI has had little impact on U.S. jobs so far, with tariffs, immigration policies and the number of college grads potentially playing a larger role. Still, AI could disrupt the workforce in the not-so-distant future.

“Future of Professionals Report” analysis: Why AI will flip law firm economics — from thomsonreuters.com by Ragunath Ramanathan
AI forces a reinvention of law firm billing models, the market will reward those firms that price by outcome, guarantee efficiency, and are transparent. The question then isn’t whether to change — it’s whether firms will stand on the sidelines or lead

Key insights:

Efficiency and cost savings are expected — AI is significantly increasing efficiency and reducing costs in the legal industry, with each lawyer expecting to save 190 work-hours per year by leveraging AI, resulting in approximately $20 billion worth of work-savings in the US alone.
Challenges to the billable hour model — The traditional billable hour model is being challenged by AI advancements, as lawyers are now able to complete tasks more efficiently and quickly, leading some law firms to explore alternative pricing models that reflect the value delivered rather than the time spent.
Opportunities for smaller law firms — AI presents unique opportunities for smaller law firms to differentiate themselves and compete with larger firms, as AI solutions allow smaller firms to access advanced technology without significant investment and deliver innovative pricing models.

The legal industry is undergoing a significant transformation that’s being driven by the rapid adoption of AI — a shift that is poised to redefine traditional practices, particularly the billable hour model, a cornerstone of law firm operations.
…
Not surprisingly, AI is anticipated to have the biggest impact on the legal industry over the next five years, with 80% of law firm survey respondents to Thomson Reuters recently published 2025 Future of Professionals report saying that they expect AI to fundamentally alter how they conduct business, especially around how law firms price, staff, and deliver legal work to their clients.

How a Gemma model helped discover a new potential cancer therapy pathway [Google]

On 10/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, experimentation, Google, health, platforms, research, science, tools, by Daniel Christian

How a Gemma model helped discover a new potential cancer therapy pathway — from blog.google by Shekoofeh Azizi and Bryan Perozzi
We’re launching a new 27 billion parameter foundation model for single-cell analysis built on the Gemma family of open models.

Today, as part of our research collaboration with Yale University, we’re releasing Cell2Sentence-Scale 27B (C2S-Scale), a new 27 billion parameter foundation model designed to understand the language of individual cells. Built on the Gemma family of open models, C2S-Scale represents a new frontier in single-cell analysis.

This announcement marks a milestone for AI in science. C2S-Scale generated a novel hypothesis about cancer cellular behavior and we have since confirmed its prediction with experimental validation in living cells. This discovery reveals a promising new pathway for developing therapies to fight cancer.

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ [Gonick]

On 10/17/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, changing business models, CMS/LMS, collaboration, colleges, community colleges, digital learning, education, education technology, emerging technologies, engagement / engaging students, experimentation, faculty/staff, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, memory, multimedia, personalized/customized learning, platforms, student-related, teaching & learning, United States, universities, vision/possibilities, by Daniel Christian

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ — from linkedin.com by Lev Gonick

Experience AI: A new architecture of learning
Experience AI represents a new architecture for learning — one that prioritizes continuity, agency and deep personalization. It fuses three dimensions into a new category of co-intelligent systems:

Agentic AI that evolves with the learner, not just serves them
Persona-based AI that adapts to individual goals, identities and motivations
Multimodal AI that engages across text, voice, video, simulation and interaction

Experience AI brings learning into context. It powers personalized, problem-based journeys where students explore ideas, reflect on progress and co-create meaning — with both human and machine collaborators.

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