human-computer interaction (HCI)

“Introducing AI assistants with memory” + other items re: AI in our learning ecosystems

On 12/01/2025, in accessibility / UDL, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, experimentation, faculty/staff, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, K-12 related, 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, memory, multimedia, personalized/customized learning, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

4 Simple & Easy Ways to Use AI to Differentiate Instruction — from mindfulaiedu.substack.com (Mindful AI for Education) by Dani Kachorsky, PhD
Designing for All Learners with AI and Universal Design Learning

So this year, I’ve been exploring new ways that AI can help support students with disabilities—students on IEPs, learning plans, or 504s—and, honestly, it’s changing the way I think about differentiation in general.

As a quick note, a lot of what I’m finding applies just as well to English language learners or really to any students. One of the big ideas behind Universal Design for Learning (UDL) is that accommodations and strategies designed for students with disabilities are often just good teaching practices. When we plan instruction that’s accessible to the widest possible range of learners, everyone benefits. For example, UDL encourages explaining things in multiple modes—written, visual, auditory, kinesthetic—because people access information differently. I hear students say they’re “visual learners,” but I think everyone is a visual learner, and an auditory learner, and a kinesthetic learner. The more ways we present information, the more likely it is to stick.

So, with that in mind, here are four ways I’ve been using AI to differentiate instruction for students with disabilities (and, really, everyone else too):

The Periodic Table of AI Tools In Education To Try Today — from ictevangelist.com by Mark Anderson

What I’ve tried to do is bring together genuinely useful AI tools that I know are already making a difference.

For colleagues wanting to explore further, I’m sharing the list exactly as it appears in the table, including website links, grouped by category below. Please do check it out, as along with links to all of the resources, I’ve also written a brief summary explaining what each of the different tools do and how they can help.

Seven Hard-Won Lessons from Building AI Learning Tools — from linkedin.com by Louise Worgan

Last week, I wrapped up Dr Philippa Hardman’s intensive bootcamp on AI in learning design. Four conversations, countless iterations, and more than a few humbling moments later – here’s what I am left thinking about.

Finally Catching Up to the New Models — from michellekassorla.substack.com by Michelle Kassorla
There are some amazing things happening out there!

An aside: Google is working on a new vision for textbooks that can be easily differentiated based on the beautiful success for NotebookLM. You can get on the waiting list for that tool by going to LearnYourWay.withgoogle.com.
…
Nano Banana Pro
Sticking with the Google tools for now, Nano Banana Pro (which you can use for free on Google’s AI Studio), is doing something that everyone has been waiting a long time for: it adds correct text to images.

Introducing AI assistants with memory — from perplexity.ai

The simple act of remembering is the crux of how we navigate the world: it shapes our experiences, informs our decisions, and helps us anticipate what comes next. For AI agents like Comet Assistant, that continuity leads to a more powerful, personalized experience.

Today we are announcing new personalization features to remember your preferences, interests, and conversations. Perplexity now synthesizes them automatically like memory, for valuable context on relevant tasks. Answers are smarter, faster, and more personalized, no matter how you work.

From DSC :
This should be important as we look at learning-related applications for AI.

For the last three days, my Substack has been in the top “Rising in Education” list. I realize this is based on a hugely flawed metric, but it still feels good. ?

– Michael G Wagner

Read on Substack

I’m a Professor. A.I. Has Changed My Classroom, but Not for the Worse. — from nytimes.com by Carlo Rotella [this should be a gifted article]
My students’ easy access to chatbots forced me to make humanities instruction even more human.

“Textbooks are no longer one-size-fits-all” [Fitzpatrick] + other items re: AI in our learning ecosystems

On 11/18/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, change, changing business models, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learner profiles, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Open AI, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, technologies for your home, training / L&D, trends, United States, universities, vendors, by Daniel Christian

Three Years from GPT-3 to Gemini 3 — from oneusefulthing.org by Ethan Mollick
From chatbots to agents

Three years ago, we were impressed that a machine could write a poem about otters. Less than 1,000 days later, I am debating statistical methodology with an agent that built its own research environment. The era of the chatbot is turning into the era of the digital coworker. To be very clear, Gemini 3 isn’t perfect, and it still needs a manager who can guide and check it. But it suggests that “human in the loop” is evolving from “human who fixes AI mistakes” to “human who directs AI work.” And that may be the biggest change since the release of ChatGPT.

Results May Vary — from aiedusimplified.substack.com by Lance Eaton, PhD
On Custom Instructions with GenAI Tools….

I’m sharing today about custom instructions and my use of them across several AI tools (paid versions of ChatGPT, Gemini, and Claude). I want to highlight what I’m doing, how it’s going, and solicit from readers to share in the comments some of their custom instructions that they find helpful.

I’ve been in a few conversations lately that remind me that not everyone knows about them, even some of the seasoned folks around GenAI and how you might set them up to better support your work. And, of course, they are, like all things GenAI, highly imperfect!

I’ll include and discuss each one below, but if you want to keep abreast of my custom instructions, I’ll be placing them here as I adjust and update them so folks can see the changes over time.

“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.
.

[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.

.
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

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.

.

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?
…
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”

Just beautiful !!#videos #morning #sunrise pic.twitter.com/DBYLjuBKO4

— Alessandro ?? NO DM (@KatanaHugo) November 8, 2025

Prompt share – ASMR draw a living animal with oil paint

Prompt: close-up shot of a hand holding a paintbrush, painting on a white sheet of paper placed on a wooden desk. As the brush glides, vivid color paint flows smoothly then suddenly transforms into living [ANIMAL] [COLOR]… pic.twitter.com/rRu6oTwzlP

— Kris Kashtanova (@icreatelife) November 7, 2025

So beautiful ??? pic.twitter.com/jBFWWRbqUq

— ???????? ????? ?? (@Hoang_HQ) November 11, 2025

BIG unveils Suzhou Museum of Contemporary Art topped with ribbon-like roof — from dezeen.com by Christina Yao
.

Also from Dezeen:

MVRDV designs giant sphere for sports arena in Tirana — from dezeen.com by Starr Charles
.

I wanted to see how #VEO3 would animate these cool story book #Midjourney images. Really great actually. I love fairytales ??? Song @sunomusic #ai #aiart #aivideo #aimusic #suno #aiimages #aifairytales pic.twitter.com/u40XfBdfWu

— Kelly Boesch???? (@kellyeld) November 6, 2025

Breaking News: Law Firm’s AI Pilot Lets New Lawyers Step Away from Billable Hours [jdjournal.com]

On 11/11/2025, in adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, human-computer interaction (HCI), ideas, innovation, intelligent systems, law schools, learning ecosystem, Legal operations, legal reform, legal technologies, legislatures / government / legal, lifelong learning, United States, workplace, by Daniel Christian

Breaking News: Law Firm’s AI Pilot Lets New Lawyers Step Away from Billable Hours — from jdjournal.com

In a groundbreaking move that may redefine how law firms integrate technology training into daily practice, Ropes & Gray LLP has introduced a new pilot program allowing its first-year associates to dedicate a significant portion of their work hours to artificial intelligence (AI) learning—without the pressure of billing those hours to clients.

The initiative, called “TrAIlblazers,” marks one of the first formal attempts by a major law firm to give attorneys credit toward their billable-hour requirements for time spent exploring and developing AI skills. The firm hopes the move will both prepare young lawyers for a rapidly evolving profession and signal a new era of flexibility in how law firms evaluate performance.

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.

…

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…

The Other Regulatory Time Bomb — from onedtech.philhillaa.com by Phil Hill
Higher ed in the US is not prepared for what’s about to hit in April for new accessibility rules

Most higher-ed leaders have at least heard that new federal accessibility rules are coming in 2026 under Title II of the ADA, but it is apparent from conversations at the WCET and Educause annual conferences that very few understand what that actually means for digital learning and broad institutional risk. The rule isn’t some abstract compliance update: it requires every public institution to ensure that all web and media content meets WCAG 2.1 AA, including the use of audio descriptions for prerecorded video. Accessible PDF documents and video captions alone will no longer be enough. Yet on most campuses, the conversation has been understood only as a buzzword, delegated to accessibility coordinators and media specialists who lack the budget or authority to make systemic changes.

And no, relying on faculty to add audio descriptions en masse is not going to happen.

The result is a looming institutional risk that few presidents, CFOs, or CIOs have even quantified.

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:

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.

Nvidia becomes first $5 trillion company [Barsee]

On 10/30/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business, computer science, corporate / business world, game-changing environment, generational differences, global / globalization, human-computer interaction (HCI), IT in HE, NVIDIA, Open AI, platforms, United States, vendors, by Daniel Christian

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:

Nvidia becomes first public company worth $5 trillion — from techcrunch.com by Ivan Mehta
The biggest beneficiary of the ongoing AI boom, Nvidia has become the first public company to pass the $5 trillion market cap milestone.

“…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.
…
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.

Adobe Reinvents its Entire Creative Suite with AI Co-Pilots, Custom Models, and a New Open Platform — from theneuron.ai by Grant Harvey
Adobe just put an AI co-pilot in every one of its apps, letting you chat with Photoshop, train models on your own style, and generate entire videos with a single subscription that now includes top models from Google, Runway, and Pika.

Adobe came to play, y’all.

At Adobe MAX 2025 in Los Angeles, the company dropped an entire creative AI ecosystem that touches every single part of the creative workflow. In our opinion, all these new features aren’t about replacing creators; it’s about empowering them with superpowers they can actually control.

Adobe’s new plan is to put an AI co-pilot in every single app.

For professionals, the game-changer is Firefly Custom Models. Start training one now to create a consistent, on-brand look for all your assets.
For everyday creators, the AI Assistants in Photoshop and Express will drastically speed up your workflow.
The best place to start is the Photoshop AI Assistant (currently in private beta), which offers a powerful glimpse into the future of creative software—a future where you’re less of a button-pusher and more of a creative director.

Adobe MAX Day 2: The Storyteller Is Still King, But AI Is Their New Superpower — from theneuron.ai by Grant Harvey
Adobe’s Day 2 keynote showcased a suite of AI-powered creative tools designed to accelerate workflows, but the real message from creators like Mark Rober and James Gunn was clear: technology serves the story, not the other way around.

On the second day of its annual MAX conference, Adobe drove home a message that has been echoing through the creative industry for the past year: AI is not a replacement, but a partner. The keynote stage featured a powerful trio of modern storytellers—YouTube creator Brandon Baum, science educator and viral video wizard Mark Rober, and Hollywood director James Gunn—who each offered a unique perspective on a shared theme: technology is a powerful tool, but human instinct, hard work, and the timeless art of storytelling remain paramount.

From DSC:
As Grant mentioned, the demos dealt with ideation, image generation, video generation, audio generation, and editing.

Adobe Max 2025: all the latest creative tools and AI announcements — from theverge.com by Jess Weatherbed

The creative software giant is launching new generative AI tools that make digital voiceovers and custom soundtracks for videos, and adding AI assistants to Express and Photoshop for web that edit entire projects using descriptive prompts. And that’s just the start, because Adobe is planning to eventually bring AI assistants to all of its design apps.

Also see Adobe Delivers New AI Innovations, Assistants and Models Across Creative Cloud to Empower Creative Professionals plus other items from the News section from Adobe

“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.
…

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.

Chegg CEO steps down amid major AI-driven restructure — from linkedin.com by Megan McDonough

Edtech firm Chegg confirmed Monday it is reducing its workforce by 45%, or 388 employees globally, and its chief executive officer is stepping down. Current CEO Nathan Schultz will be replaced effective immediately by executive chairman (and former CEO) Dan Rosensweig. The rise of AI-powered tools has dealt a massive blow to the online homework helper and led to “substantial” declines in revenue and traffic. Company shares have slipped over 10% this year. Chegg recently explored a possible sale, but ultimately decided to keep the company intact.

At the most recent NVIDIA GTC conference, held in Washington, D.C. in October 2025, CEO Jensen Huang announced major developments emphasizing the use of AI to “reindustrialize America”. This included new partnerships, expansion of the Blackwell architecture, and advancements in AI factories for robotics and science. The spring 2024 GTC conference, meanwhile, was headlined by the launch of the Blackwell GPU and significant updates to the Omniverse and robotics platforms.

During the keynote in D.C., Jensen Huang focused on American AI leadership and announced several key initiatives.

Massive Blackwell GPU deployments: The company announced an expansion of its Blackwell GPU architecture, which first launched in March 2024. Reportedly, the company has already shipped 6 million Blackwell chips, with orders for 14 million more by the end of 2025.
AI supercomputers for science: In partnership with the Department of Energy and Oracle, NVIDIA is building new AI supercomputers at Argonne National Laboratory. The largest, named “Solstice,” will deploy 100,000 Blackwell GPUs.
6G infrastructure: NVIDIA announced a partnership with Nokia to develop a U.S.-based, AI-native 6G technology stack.
AI factories for robotics: A new AI Factory Research Center in Virginia will use NVIDIA’s technology for building massive-scale data centers for AI.
Autonomous robotaxis: The company’s self-driving technology, already adopted by several carmakers, will be used by Uber for an autonomous fleet of 100,000 robotaxis starting in 2027.

Nvidia and Uber team up to develop network of self-driving cars — from finance.yahoo.com by Daniel Howley

Nvidia (NVDA) and Uber (UBER) on Tuesday revealed that they’re working to put together what they say will be the world’s largest network of Level 4-ready autonomous cars.

The duo will build out 100,000 vehicles beginning in 2027 using Nvidia’s Drive AGX Hyperion 10 platform and Drive AV software.

Nvidia stock hits all-time high, nears $5 trillion market cap after slew of updates at GTC event — from finance.yahoo.com by Daniel Howley

Nvidia (NVDA) stock on Tuesday rose 5% to close at a record high after the company announced a slew of product updates, partnerships, and investment initiatives at its GTC event in Washington, D.C., putting it on the doorstep of becoming the first company in history with a market value above $5 trillion.

The AI chip giant is approaching the threshold — settling at a market cap of $4.89 trillion on Tuesday — just months after becoming the first to close above $4 trillion in July.

Learning Ecosystems

Announcements from Adobe — esp. focused on AI

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