Artificial Intelligence/Agents/LLMs/and Related

Beyond ChatGPT: Why In-House Counsel Need Purpose Built AI (Cecilia Ziniti, CEO – GC AI)

On 12/04/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, tools, trends, United States, vendors, by Daniel Christian

Beyond ChatGPT: Why In-House Counsel Need Purpose Built AI (Cecilia Ziniti, CEO – GC AI) — from tlpodcast.com

This episode features a conversation with Cecilia Ziniti, Co-Founder and CEO of GC.AI. Cecilia traces her career from the early days of the internet to founding an AI-driven legal platform for in-house counsel.

Cecilia shares her journey, starting as a paralegal at Yahoo in the early 2000s, working on nascent legal issues related to the internet. She discusses her time at Morrison & Foerster and her role at Amazon, where she was an early member of the Alexa team, gaining deep insight into AI’s potential before the rise of modern large language models (LLMs).

The core discussion centers on the creation of GC AI, a legal AI tool specifically designed for in-house counsel. Cecilia explains why general LLMs like ChatGPT are insufficient for professional legal work—lacking proper citation, context, and security/privilege protections. She highlights the app’s features, including enhanced document analysis (RAG implementation), a Word Add-in, and workflow-based playbooks to deliver accurate, client-forward legal analysis. The episode also touches on the current state of legal tech, the growing trend of bringing legal work in-house, and the potential for AI to shift the dynamics of the billable hour.

Agents, robots, and us: Skill partnerships in the age of AI — from mckinsey.com by Lareina Yee, Anu Madgavkar, Sven Smit, Alexis Krivkovich, Michael Chui, María Jesús Ramírez, and Diego Castresana
AI is expanding the productivity frontier. Realizing its benefits requires new skills and rethinking how people work together with intelligent machines.

At a glance

Work in the future will be a partnership between people, agents, and robots—all powered by AI. …
Most human skills will endure, though they will be applied differently. …
Our new Skill Change Index shows which skills will be most and least exposed to automation in the next five years….
Demand for AI fluency—the ability to use and manage AI tools—has grown sevenfold in two years…
By 2030, about $2.9 trillion of economic value could be unlocked in the United States…

Also related/see:

The state of AI in 2025: Agents, innovation, and transformation — from mckinsey.com
Almost all survey respondents say their organizations are using AI, and many have begun to use AI agents. But most are still in the early stages of scaling AI and capturing enterprise-level value.

State of AI: December 2025 newsletter — from nathanbenaich.substack.com by Nathan Benaich
What you’ve got to know in AI from the last 4 weeks.

Welcome to the latest issue of the State of AI, an editorialized newsletter that covers the key developments in AI policy, research, industry, and start-ups over the last month.

“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.

Some very sharp creativity!

On 11/30/2025, in architecture, art, Artificial Intelligence/Agents/LLMs/and Related, Asia, content development, aggregation, repositories, creativity, digital photography, photography, tools, visualizing information, by Daniel Christian

Enjoy your weekend and your coffee, loves ?? ?? pic.twitter.com/GmLFHcHFWt

— Kris Kashtanova (@icreatelife) November 22, 2025

A holographic table that makes every traditional presentation look outdated. pic.twitter.com/CxxurXYp6v

— Architecture Presentation (@arcpresentation) November 23, 2025

“Whither Rivers Flow” by Photographer Ximeng Tu — from booooooom.com by Ximeng Tu

Zaha Hadid Architects completes waterfront stadium and sports centre in Guangzhou — from dezeen.com by Amy Peacock

Law Firm 2.0: A Trillion-Dollar Market Begins To Move — from abovethelaw.com by Ken Crutchfield
The test cases for Law Firm 2.0 are arriving faster than many expected.

A move to separate legal advice from other legal services that don’t require advice is a big shift that would ripple through established firms and also test regulatory boundaries.
…
The LegalTech Fund (TLTF) sees a $1 trillion opportunity to reinvent legal services through the convergence of technology, regulatory changes, and innovation. TLTF calls this movement Law Firm 2.0, and the fund believes a reinvention will pave the way for entirely new, tech-enabled models of legal service delivery.

From Paper to Platform: How LegalTech Is Revolutionizing the Practice of Law — from markets.financialcontent.com by AB Newswire

For decades, practicing law has been a business about paper — contracts, case files, court documents, and floor-to-ceiling piles of precedent. But as technology transforms all aspects of modern-day business, law firms and in-house legal teams are transforming along with it. The development of LegalTech has revolutionized what was previously a paper-driven, manpower-intensive profession into a data-driven digital web of collaboration and automation.

Conclusion: Building the Future of Law
The practice of law has always been about accuracy, precedent, and human beings. Technology doesn’t alter that — it magnifies it. The shift to the platform from paper is about liberating lawyers from back-office tasks so they can concentrate on strategy, advocacy, and creativity.

By coupling intelligent automation with moral obligation, today’s firms are positioning the legal profession for a more intelligent, responsive industry. LegalTech isn’t about automation, it’s about empowering attorneys to practice at the speed of today’s business.

What Legal Can Learn from Other Industries’ AI Transformations — from jdsupra.com

Artificial intelligence has already redefined how industries like finance, healthcare, and supply chain operate — transforming once-manual processes into predictive, data-driven engines of efficiency.

Yet the legal industry, while increasingly open to innovation, still lags behind its peers in adopting automation at scale. As corporate legal departments face mounting pressure to do more with less, they have an opportunity to learn from how other sectors successfully integrated AI into their operations.

The message is clear: AI transformation doesn’t just change workflows — it changes what’s possible.

7 Legal Tech Trends To Watch In 2026 — from lexology.com

Small Language Models Are Changing Legal Tech: What That Means for Lawyers and Law Firms — from community.nasscom.in

The legal profession is at a turning point. Artificial intelligence tools are moving from novelty to everyday utility, and small language models, or SLMs, are a major reason why. For law firms and in-house legal teams that are balancing client confidentiality, tight budgets, and the need to move faster, SLMs offer a practical, high impact way to bring legal AI into routine practice. This article explains what SLMs are, why they matter to lawyers, where they fit in legal workflows, and how to adopt them responsibly.

Legal AI startup draws new $50 million Blackstone investment, opens law firm — from reuters.com by Sara Merken

NEW YORK, Nov 20 (Reuters) – Asset manager Blackstone (BX.N), opens new tab has invested $50 million in Norm Ai, a legal and compliance technology startup that also said on Thursday that it is launching an independent law firm that will offer “AI-native legal services.”

Lawyers at the new New York-based firm, Norm Law LLP, will use Norm Ai’s artificial intelligence technology to do legal work for Blackstone and other financial services clients, said Norm Ai founder and CEO John Nay.

Law School Toolbox Podcast Episode 531: What Law Students Should Know About New Legal Tech (w/Gabe Teninbaum) — from jdsupra.com

Today, Alison and Gabe Teninbaum — law professor and creator of SpacedRepetition.com — discuss how technology is rapidly transforming the legal profession, emphasizing the importance for law students and lawyers to develop technological competence and adapt to new tools and roles in the legal profession.

New York is the San Francisco of legal tech — from businessinsider.com by Melia Russell

Legal tech ?? NYC.
To win the market, startups say they need to be where the law firms and corporate legal chiefs are.
Legora and Harvey are expanding their footprints in New York, as Clio hunts for office space.

Legal Tech Startups Expand in New York to Access Law Firms — from indexbox.io

Several legal technology startups are expanding their physical presence in New York City, according to a report from Legal tech NYC. The companies state that to win market share, they need to be located where major law firms and corporate legal departments are based.

Linklaters unveils 20-strong ‘AI lawyer’ team — from legalcheek.com by Legal Cheek

Magic Circle giant Linklaters has launched a team of 20 ‘AI Lawyers’ (yes, that is their actual job title) as it ramps up its commitment to artificial intelligence across its global offices.

The new cohort is a mix of external tech specialists and Linklaters lawyers who have decided to boost their legal expertise with advanced AI know-how. They will be placed into practice groups around the world to help build prompts, workflows and other tech driven processes that the firm hopes will sharpen client delivery.

I went to a closed-door retreat for top lawyers. The message was clear: Don’t fear AI — use it. — from businessinsider.com by Melia Russell

AI is making its mark on law firms and corporate legal teams.
Clients expect measurable savings, and firms are spending real money to deliver them.
At TLTF Summit, Big Law leaders and legal-tech builders explored the future of the industry.

From Cost Center to Command Center: The Future of Litigation is Being Built In-House — from law.stanford.edu by Adam Rouse, Tamra Moore, Renee Meisel, Kassi Burns, & Olga Mack

Litigation isn’t going away, but who leads, drafts, and drives it is rapidly changing. Empirical research shows corporate legal departments have steadily expanded litigation management functions over the past decade. (Annual Litigation Trends Survey, Norton Rose Fulbright (2025)).

For decades, litigation lived squarely in the law firm domain. (Wald, Eli, Getting in and Out of the House: Career Trajectories of In-House Lawyers, Fordham Law Review, Vol. 88, No. 1765, 2020 (June 22, 2020)). Corporate legal departments played a responsive role: approving strategies, reviewing documents, and paying hourly rates. But through dozens of recent conversations with in-house legal leaders, legal operations professionals, and litigation specialists, a new reality is emerging. One in which in-house counsel increasingly owns the first draft, systematizes their litigation approach, and reshapes how outside counsel fits into the picture.

AI, analytics, exemplar libraries, playbooks, and modular document builders are not simply tools. They are catalysts for a structural shift. Litigation is becoming modular, data-informed, and orchestrated by in-house teams who increasingly want more than cost control. They want consistency, clarity, and leverage. This piece outlines five major trends from our qualitative research, predictions on their impact to the practice of law, and research questions that are worth considering to further understand these trends. A model is then introduced for understanding how litigation workflows and outside counsel relationships will evolve in the coming years.

“The AI opportunity in L&D isn’t one thing – it’s five different capability unlocks.” [Vinauskaite] + other items re: AI in our LE’s

On 11/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, business, cloud-based computing / apps / other cloud-related, colleges, community colleges, corporate / business world, corporate universities / corporate training, digital learning, emerging technologies, faculty/staff, game-changing environment, higher education, innovation, instructional design, learning agents, learning ecosystem, Learning Experience Design, memory, online learning, Open AI, pedagogy, platforms, productivity / tips and tricks, professional development, simulations, skills, student-related, teachers, teaching & learning, tools, training / L&D, United States, universities, workplace, by Daniel Christian

AI’s Role in Online Learning > Take It or Leave It with Michelle Beavers, Leo Lo, and Sara McClellan — from intentionalteaching.buzzsprout.com by Derek Bruff

You’ll hear me briefly describe five recent op-eds on teaching and learning in higher ed. For each op-ed, I’ll ask each of our panelists if they “take it,” that is, generally agree with the main thesis of the essay, or “leave it.” This is an artificial binary that I’ve found to generate rich discussion of the issues at hand.

Could Your Next Side Hustle Be Training AI? — from builtin.com by Jeff Rumage
As automation continues to reshape the labor market, some white-collar professionals are cashing in by teaching AI models to do their jobs.

Summary: Artificial intelligence may be replacing jobs, but it’s also creating some new ones. Professionals in fields like medicine, law and engineering can earn big money training AI models, teaching them human skills and expertise that may one day make those same jobs obsolete.

DEEP DIVE: The AI user interface of the future = Voice — from theneurondaily.com by Grant Harvey
PLUS: Gemini 3.0 and Microsoft’s new voice features

Here’s the thing: voice is finally good enough to replace typing now. And I mean actually good enough, not “Siri, play Despacito” good enough.

To Paraphrase Andrej Karpathy’s famous quote, “the hottest new programming language is English”, in this case, the hottest new user interface is talking.

The Great Convergence: Why Voice Is Having Its Moment
Three massive shifts just collided to make voice interfaces inevitable.

1. First, speech recognition stopped being terrible. …
2. Second, our devices got ears everywhere. …
3. Third, and most importantly: LLMs made voice assistants smart enough to be worth talking to. …

Introducing group chats in ChatGPT — from openai.com
Collaborate with others, and ChatGPT, in the same conversation.

Update on November 20, 2025: Early feedback from the pilot has been positive, so we’re expanding group chats to all logged-in users on ChatGPT Free, Go, Plus and Pro plans globally over the coming days. We will continue refining the experience as more people start using it.

Today, we’re beginning to pilot a new experience in a few regions that makes it easy for people to collaborate with each other—and with ChatGPT—in the same conversation. With group chats, you can bring friends, family, or coworkers into a shared space to plan, make decisions, or work through ideas together.

Whether you’re organizing a group dinner or drafting an outline with coworkers, ChatGPT can help. Group chats are separate from your private conversations, and your personal ChatGPT memory is never shared with anyone in the chat.

“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.

Disrupting the first reported AI-orchestrated cyber espionage campaign [Anthropic]

On 11/17/2025, in Artificial Intelligence/Agents/LLMs/and Related, Asia, dangers of the status quo, Europe, game-changing environment, global / globalization, IT in HE, platforms, policy, political science, society, the downsides of how people use tech, UK, United States, vendors, by Daniel Christian

Disrupting the first reported AI-orchestrated cyber espionage campaign — from Anthropic

Executive summary
We have developed sophisticated safety and security measures to prevent the misuse of our AI models. While these measures are generally effective, cybercriminals and other malicious actors continually attempt to find ways around them. This report details a recent threat campaign we identified and disrupted, along with the steps we’ve taken to detect and counter this type of abuse. This represents the work of Threat Intelligence: a dedicated team at Anthropic that investigates real world cases of misuse and works within our Safeguards organization to improve our defenses against such cases.

In mid-September 2025, we detected a highly sophisticated cyber espionage operation conducted by a Chinese state-sponsored group we’ve designated GTG-1002 that represents a fundamental shift in how advanced threat actors use AI. Our investigation revealed a well-resourced, professionally coordinated operation involving multiple simultaneous targeted intrusions. The operation targeted roughly 30 entities and our investigation validated a handful of successful intrusions.

This campaign demonstrated unprecedented integration and autonomy of AI throughout the attack lifecycle, with the threat actor manipulating Claude Code to support reconnaissance, vulnerability discovery, exploitation, lateral movement, credential harvesting, data analysis, and exfiltration operations largely autonomously. The human operator tasked instances of Claude Code to operate in groups as autonomous penetration testing orchestrators and agents, with the threat actor able to leverage AI to execute 80-90% of tactical operations independently at physically impossible request rates.

From DSC:
The above item was from The Rundown AI, who wrote the following:

The Rundown: Anthropic thwarted what it believes is the first AI-driven cyber espionage campaign, after attackers were able to manipulate Claude Code to infiltrate dozens of organizations, with the model executing 80-90% of the attack autonomously.

The details:

The September 2025 operation targeted roughly 30 tech firms, financial institutions, chemical manufacturers, and government agencies.
The threat was assessed with ‘high confidence’ to be a Chinese state-sponsored group, using AI’s agentic abilities to an “unprecedented degree.”
Attackers tricked Claude by splitting malicious tasks into smaller, innocent-looking requests, claiming to be security researchers pushing authorized tests.
The attacks mark a major step up from Anthropic’s “vibe hacking” findings in June, now requiring minimal human oversight beyond strategic approval.

Why it matters: Anthropic calls this the “first documented case of a large-scale cyberattack executed without substantial human intervention”, and AI’s agentic abilities are creating threats that move and scale faster than ever. While AI capabilities can also help prevent them, security for organizations worldwide likely needs a major overhaul.

Also see:

Disrupting the first reported AI-orchestrated cyber espionage campaign — from anthropic.com via The AI Valley

We recently argued that an inflection point had been reached in cybersecurity: a point at which AI models had become genuinely useful for cybersecurity operations, both for good and for ill. This was based on systematic evaluations showing cyber capabilities doubling in six months; we’d also been tracking real-world cyberattacks, observing how malicious actors were using AI capabilities. While we predicted these capabilities would continue to evolve, what has stood out to us is how quickly they have done so at scale.

Chinese Hackers Used AI to Run a Massive Cyberattack on Autopilot (And It Actually Worked) — from theneurondaily.com

Why this matters: The barrier to launching sophisticated cyberattacks just dropped dramatically. What used to require entire teams of experienced hackers can now be done by less-skilled groups with the right AI setup.

This is a fundamental shift. Over the next 6-12 months, expect security teams everywhere to start deploying AI for defense—automation, threat detection, vulnerability scanning at a more elevated level. The companies that don’t adapt will be sitting ducks to get overwhelmed by similar tricks.

If your company handles sensitive data, now’s the time to ask your IT team what AI-powered defenses you have in place. Because if the attackers are using AI agents, you’d better believe your defenders need them too…

I analyzed 180M jobs to see what jobs AI is actually replacing today [Wing Chiu]

On 11/13/2025, in Artificial Intelligence/Agents/LLMs/and Related, career development, change, computer science, corporate / business world, leadership, marketing/social marketing, programming, trends, workplace, by Daniel Christian

I analyzed 180M jobs to see what jobs AI is actually replacing today — from bloomberry.com by Henley Wing Chiu; via Kim Isenberg

I analyzed nearly 180 million global job postings from January 2023 to October 2025, using data from Revealera, a provider of jobs data. While I acknowledge not all job postings result in a hire, and some are ‘ghost jobs’, since I was comparing the relative growth in job titles, this didn’t seem like a big issue to me.

I simply wanted to know which specific job titles declined or grew the most in 2025, compared to 2024. Because those were likely to be ones that AI is impacting the most.

Key Sections

Also from Kim Isenberg, see:

October Layoffs Were the Worst in 22 Years and Hit Tech Workers Hard — from gizmodo.com by Lucas Ropek
For coders, October royally sucked.

“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.

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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?
…
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
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Also from Dezeen:

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

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