platforms

Firefly adds new video capabilities, industry leading AI models, and Generate Sound Effects feature — from blog.adobe.com

Today, we’re introducing powerful enhancements to our Firefly Video Model, including improved motion fidelity and advanced video controls that will accelerate your workflows and provide the precision and style you need to elevate your storytelling. We are also adding new generative AI partner models within Generate Video on Firefly, giving you the power to choose which model works best for your creative needs across image, video and sound.

Plus, our new workflow tools put you in control of your video’s composition and style. You can now layer in custom-generated sound effects right inside the Firefly web app — and start experimenting with AI-powered avatar-led videos.
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Generate Sound Effects (beta)
Sound is a powerful storytelling tool that adds emotion and depth to your videos. Generate Sound Effects (beta) makes it easy to create custom sounds, like a lion’s roar or ambient nature sounds, that enhance your visuals. And like our other Firefly generative AI models, Generate Sound Effects (beta) is commercially safe, so you can create with confidence.

Just type a simple text prompt to generate the sound effect you need. Want even more control? Use your voice to guide the timing and intensity of the sound. Firefly listens to the energy and rhythm of your voice to place sound effects precisely where they belong — matching the action in your video with cinematic timing.

The type of functionality found in MyNextChapter.ai could work very well in a next-gen learning platform [Christian]

On 07/24/2025, in 21st century, 24x7x365 access, adult learning, Alternatives, apprenticeships, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, cloud-based computing / apps / other cloud-related, colleges, communications, community colleges, corporate / business world, Daniel S. Christian, emerging technologies, experimentation, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, passions, pathways, personalized/customized learning, platforms, professional development, reinvent, skills, social learning / networks, society, staying relevant, surviving, teachers, teaching & learning, teaching online, technologies for your home, tools, United States, universities, vendors, vision/possibilities, vocational / trades, by Daniel Christian

From DSC:
In looking at MyNextChapter.ai — THIS TYPE OF FUNCTIONALITY of an AI-based chatbot talking to you re: good fits for a future job — is the kind of thing that could work well in this type of vision/learning platform. The AI asks you relevant career-oriented questions, comes up with some potential job fits, and then gives you resources about how to gain those skills, who to talk with, organizations to join, next steps to get your foot in the door somewhere, etc.

The next gen learning platform would provide links to online-based courses, blogs, peoples’ names on LinkedIn, courses from L&D organizations or from institutions of higher education or from other entities/places to obtain those skills (similar to the ” Action Plan” below from MyNextChapter.ai).

Introducing ChatGPT agent: bridging research and action [OpenAI]

On 07/19/2025, in corporate / business world, emerging technologies, experimentation, innovation, intelligent systems, learning agents, Open AI, platforms, productivity / tips and tricks, research, tools, vendors, by Daniel Christian

Introducing ChatGPT agent: bridging research and action — from openai.com
ChatGPT now thinks and acts, proactively choosing from a toolbox of agentic skills to complete tasks for you using its own computer.

ChatGPT can now do work for you using its own computer, handling complex tasks from start to finish.

You can now ask ChatGPT to handle requests like “look at my calendar and brief me on upcoming client meetings based on recent news,” “plan and buy ingredients to make Japanese breakfast for four,” and “analyze three competitors and create a slide deck.” ChatGPT will intelligently navigate websites, filter results, prompt you to log in securely when needed, run code, conduct analysis, and even deliver editable slideshows and spreadsheets that summarize its findings.

PODCAST: Did AI “break” school? Or will it “fix” it? …and if so, what can we do about it? [Noles & Harvey]

On 07/19/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, change, content development, aggregation, repositories, digital learning, education, education reform, education technology, emerging technologies, experimentation, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, Open AI, pedagogy, platforms, podcasting, productivity / tips and tricks, skills, society, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, by Daniel Christian

PODCAST: Did AI “break” school? Or will it “fix” it? …and if so, what can we do about it? — from theneurondaily.com by Grant Harvey, Corey Noles, Grant Harvey, & Matthew Robinson

In Episode 5 of The Neuron Podcast, Corey Noles and Grant Harvey tackle the education crisis head-on. We explore the viral UCLA “CheatGPT” controversy, MIT’s concerning brain study, and innovative solutions like Alpha School’s 2-hour learning model. Plus, we break down OpenAI’s new $10M teacher training initiative and share practical tips for using AI to enhance learning rather than shortcut it. Whether you’re a student, teacher, or parent, you’ll leave with actionable insights on the future of education.

AI is rewiring how we learn, and it’s a game-changer for L&D— from chieflearningofficer.com by Josh Bersin
As AI becomes central to learner engagement, L&D leaders are being urged to fundamentally rethink corporate training, says global industry analyst Josh Bersin.

What are people really doing with ChatGPT? They’re learning. They’re asking questions, getting immediate answers, digging deeper, analyzing information and ultimately making themselves more productive. So, one could argue that simply by shifting to a “learn by inquiry” model, we may triple our value to the business.

From my experience, there are two main learning models in this industry. The first is “what you need to know”—linear or prescriptive things that every employee needs to understand about the company, its products and their role. This kind of content is well handled by existing L&D models.

The second, and far more important, is “what you’d like to know”—questions, curiosities and explorations about how the company works, what customers truly need and how we can each go further in our careers. Thanks to AI, this kind of learning is now explosive and transformative.

Imagine a sales rep who loses a deal. Naturally, they may ask, “What could I have done to be more successful?” A well-designed AI-powered learning system would take that question, give the employee an initial answer and chat with the individual to dig into the problem.

The system would then surface relevant sales training material and recommend videos, tips or case studies for help. And the employee, assuming they like the experience, would likely keep exploring until they feel they’ve learned what they need.

This “curiosity-based” learning is now possible, and its benefits extend far beyond traditional training.

“Why do we treat the syllabus like a liability waiver instead of a roadmap?” [Poff]

On 07/12/2025, in adjunct faculty, colleges, community colleges, computer science, content development, aggregation, repositories, digital learning, digital video, education, education technology, engagement / engaging students, experimentation, faculty/staff, Google, higher education, history, homeschooling/homeschoolers, ideas, instructional design, K-12 related, languages and translation, learning, Learning Experience Design, learning hubs & pods & microschooling, learning preferences, learning spaces, mathematics, parents/guardians, pedagogy, platforms, productivity / tips and tricks, programming, science, STEAM-related, student-related, teachers, teaching & learning, technologies for your home, tools, United States, universities, writing, youth, by Daniel Christian

Speaking of items involving teaching and learning, also see:

Transform Public Speaking with Yoodli: Your AI Coach — from rdene915.com by Paula Johnson

Yoodli is an AI tool designed to help users improve their public speaking skills. It analyzes your speech in real-time or after a recording and gives you feedback on things like:

- Filler words (“um,” “like,” “you know”)
- Pacing (Are you sprinting or sedating your audience?)
- Word choice and sentence complexity
- Eye contact and body language (with video)
- And yes, even your “uhhh” to actual word ratio

Yoodli gives you a transcript and a confidence score, plus suggestions that range from helpful to brutally honest. It’s basically Simon Cowell with AI ethics and a smiley face interface.

[What’s] going on with AI and education? — from theneuron.ai by Grant Harvey
With students and teachers alike using AI, schools are facing an “assessment crisis” where the line between tool and cheating has blurred, forcing a shift away from a broken knowledge economy toward a new focus on building human judgment through strategic struggle.

What to do about it: The future belongs to the “judgment economy,” where knowledge is commoditized but taste, agency, and learning velocity become the new human moats. Use the “Struggle-First” principle: wrestle with problems for 20-30 minutes before turning to AI, then use AI as a sparring partner (not a ghostwriter) to deepen understanding. The goal isn’t to avoid AI, but to strategically choose when to embrace “desirable difficulties” that build genuine expertise versus when to leverage AI for efficiency.
…
The Alpha-School Program in brief:

- Students complete core academics in just 2 hours using AI tutors, freeing up 4+ hours for life skills, passion projects, and real-world experiences.
- The school claims students learn at least 2x faster than their peers in traditional school.
- The top 20% of students show 6.5x growth. Classes score in the top 1-2% nationally across the board.
- Claims are based on NWEA’s Measures of Academic Progress (MAP) assessments… with data only available to the school. Hmm…

Austen Allred shared a story about the school, which put it on our radar.

Featured Report: Teaching for Tomorrow: Unlocking Six Weeks a Year With AI — from gallup.com
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In the latest installment of Gallup and the Walton Family Foundation’s research on education, K-12 teachers reveal how AI tools are transforming their workloads, instructional quality and classroom optimism. The report finds that 60% of teachers used an AI tool during the 2024–25 school year. Weekly AI users report reclaiming nearly six hours per week — equivalent to six weeks per year — which they reinvest in more personalized instruction, deeper student feedback and better parent communication.

Despite this emerging “AI dividend,” adoption is uneven: 40% of teachers aren’t using AI at all, and only 19% report their school has a formal AI policy. Teachers with access to policies and support save significantly more time.

Educators also say AI improves their work. Most report higher-quality lesson plans, assessments and student feedback. And teachers who regularly use AI are more optimistic about its benefits for student engagement and accessibility — mirroring themes from the Voices of Gen Z: How American Youth View and Use Artificial Intelligence report, which found students hesitant but curious about AI’s classroom role. As AI tools grow more embedded in education, both teachers and students will need the training and support to use them effectively.

Also see:

2-Hour Learning
- What if children could crush academics in 2 hours, 2x faster?
- What if children could get back their most valuable resource, which is time?
- What if children could pursue the things they want during their afternoons and develop life skills?

Amira Learning: Teaching With The AI-Powered Reading Tool — from techlearning.com by Erik Ofgang
Amira Learning is a research-backed AI reading tutor that incorporates the science of reading into its features.

What Is Amira Learning?
Amira Learning’s system is built upon research led by Jack Mostow, a professor at Carnegie Mellon who helped pioneer AI literacy education. Amira uses Claude AI to power its AI features, but these features are different than many other AI tools on the market. Instead of focusing on chat and generative response, Amira’s key feature is its advanced speech recognition and natural language processing capabilities, which allow the app to “hear” when a student is struggling and tailor suggestions to that student’s particular mistakes.

Though it’s not meant to replace a teacher, Amira provides real-time feedback and also helps teachers pinpoint where a student is struggling. For these reasons, Amira Learning is a favorite of education scientists and advocates for science of reading-based literacy instruction. The tool currently is used by more than 4 million students worldwide and across the U.S.

What enterprise leaders can learn from LinkedIn’s success with AI agents [Plumb]

On 06/27/2025, in Artificial Intelligence/Agents/LLMs/and Related, business, career development, cloud-based computing / apps / other cloud-related, Microsoft, platforms, productivity / tips and tricks, strategy, tools, United States, vendors, workplace, by Daniel Christian

What enterprise leaders can learn from LinkedIn’s success with AI agents — from venturebeat.com by Taryn Plumb

LinkedIn is taking a multi-agent approach, using what Agarwal described as a collection of agents collaborating to get the job done. A supervisor agent orchestrates all the tasks among other agents, including intake and sourcing agents that are “good at one and only one job.”

All communication occurs through the supervisor agent, which receives input from human users regarding role qualifications and other details. That agent then provides context to a sourcing agent, which culls through recruiter search stacks and sources candidates along with descriptions on why they might be a good fit for the job. That information is then returned to the supervisor agent, which begins actively interacting with the human user.

“Then you can collaborate with it, right?” said Agarwal. “You can modify it. No longer do you have to talk to the platform in keywords. You can talk to the platform in natural language, and it’s going to answer you back, it’s going to have a conversation with you.”

2025 Learning System Top Picks — from elearninfo247.com by Craig Weiss

Who is leading the pack? Who is setting themselves apart here in the mid-year?

Are they an LMS? LMS/LXP? Talent Development System? Mentoring? Learning Platform?

Something else?

Are they solely customer training/education, mentoring, or coaching? Are they focused only on employees? Are they an amalgamation of all or some?

Well, they cut across the board – hence, they slide under the “Learning Systems” umbrella, which is under the bigger umbrella term – “Learning Technology.”
…
Categories: L&D-specific, Combo (L&D and Training, think internal/external audiences), and Customer Training/Education (this means customer education, which some vendors use to mean the same as customer training).

“The résumé is dying, and AI is holding the smoking gun” [Edwards] + other items re: AI in general

On 06/25/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, career development, cloud-based computing / apps / other cloud-related, emerging technologies, game-changing environment, human-computer interaction (HCI), innovation, Open AI, platforms, trends, United States, workplace, by Daniel Christian

The résumé is dying, and AI is holding the smoking gun — from arstechnica.com by Benj Edwards
As thousands of applications flood job posts, ‘hiring slop’ is kicking off an AI arms race.

Employers are drowning in AI-generated job applications, with LinkedIn now processing 11,000 submissions per minute—a 45 percent surge from last year, according to new data reported by The New York Times.

Due to AI, the traditional hiring process has become overwhelmed with automated noise. It’s the résumé equivalent of AI slop—call it “hiring slop,” perhaps—that currently haunts social media and the web with sensational pictures and misleading information. The flood of ChatGPT-crafted résumés and bot-submitted applications has created an arms race between job seekers and employers, with both sides deploying increasingly sophisticated AI tools in a bot-versus-bot standoff that is quickly spiraling out of control.

The Times illustrates the scale of the problem with the story of an HR consultant named Katie Tanner, who was so inundated with over 1,200 applications for a single remote role that she had to remove the post entirely and was still sorting through the applications three months later.

Job seekers are leaning into AI — and other happenings in the world of work — from LinkedIn News

Job growth is slowing — and for many professionals, that means longer job hunts and more competition. As a result, more job seekers are turning to AI to streamline their search and stand out.

From optimizing resumes to preparing for interviews, AI tools are becoming a key part of today’s job hunt. Recruiters say it’s getting harder to sift through application materials and identify what is AI-generated and decipher which applicants are actually qualified — but they also say they prefer candidates with AI skills.

The result? Job seekers are growing their familiarity with AI faster than their non-job-seeking counterparts and it’s shifting how they view the workplace. According to LinkedIn’s latest Workforce Confidence survey, over half of active job seekers (52%) believe AI will eventually take on some of the mundane, manual tasks that they’re currently focused on, compared to 46% of others not actively job seeking.

OpenAI warns models with higher bioweapons risk are imminent — from axios.com by Ina Fried

OpenAI cautioned Wednesday that upcoming models will head into a higher level of risk when it comes to the creation of biological weapons — especially by those who don’t really understand what they’re doing.

Why it matters: The company, and society at large, need to be prepared for a future where amateurs can more readily graduate from simple garage weapons to sophisticated agents.

Driving the news: OpenAI executives told Axios the company expects forthcoming models will reach a high level of risk under the company’s preparedness framework.

- As a result, the company said in a blog post, it is stepping up the testing of such models, as well as including fresh precautions designed to keep them from aiding in the creation of biological weapons.
- OpenAI didn’t put an exact timeframe on when the first model to hit that threshold will launch, but head of safety systems Johannes Heidecke told Axios “We are expecting some of the successors of our o3 (reasoning model) to hit that level.”

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Agentic AI use cases in the legal industry — from legal.thomsonreuters.com
What legal professionals need to know now with the rise of agentic AI

While GenAI can create documents or answer questions, agentic AI takes intelligence a step further by planning how to get multi-step work done, including tasks such as consuming information, applying logic, crafting arguments, and then completing them.? This leaves legal teams more time for nuanced decision-making, creative strategy, and relationship-building with clients—work that machines can’t do.

The AI Legal Landscape in 2025: Beyond the Hype — from akerman.com by Melissa C. Koch

What we’re witnessing is a profession in transition where specific tasks are being augmented or automated while new skills and roles emerge.

The data tells an interesting story: approximately 79% of law firms have integrated AI tools into their workflows, yet only a fraction have truly transformed their operations. Most implementations focus on pattern recognition tasks such as document review, legal research, contract analysis. These implementations aren’t replacing lawyers; they’re redirecting attention to higher-value work.

This technological shift doesn’t happen in isolation. It’s occurring amid client pressure for efficiency, competition from alternative providers, and the expectations of a new generation of lawyers who have never known a world without AI assistance.

LexisNexis and Harvey team up to revolutionize legal research with artificial intelligence — from abajournal.com by Danielle Braff

Lawyers using the Harvey artificial intelligence platform will soon be able to tap into LexisNexis’ vast legal research capabilities.

Thanks to a new partnership announced Wednesday, Harvey users will be able to ask legal questions and receive fast, citation-backed answers powered by LexisNexis case law, statutes and Shepard’s Citations, streamlining everything from basic research to complex motions. According to a press release, generated responses to user queries will be grounded in LexisNexis’ proprietary knowledge graphs and citation tools—making them more trustworthy for use in court or client work.

10 Legal Tech Companies to Know — from builtin.com
These companies are using AI, automation and analytics to transform how legal work gets done.
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Four months after a $3B valuation, Harvey AI grows to $5B — from techcrunch.com by Marina Temkin

Harvey AI, a startup that provides automation for legal work, has raised $300 million in Series E funding at a $5 billion valuation, the company told Fortune. The round was co-led by Kleiner Perkins and Coatue, with participation from existing investors, including Conviction, Elad Gil, OpenAI Startup Fund, and Sequoia.

The billable time revolution — from jordanfurlong.substack.com by Jordan Furlong
Gen AI will bring an end to the era when lawyers’ value hinged on performing billable work. Grab the coming opportunity to re-prioritize your daily activities and redefine your professional purpose.

Because of Generative AI, lawyers will perform fewer “billable” tasks in future; but why is that a bad thing? Why not devote that incoming “freed-up” time to operating, upgrading, and flourishing your law practice? Because this is what you do now: You run a legal business. You deliver good outcomes, good experiences, and good relationships to clients. Humans do some of the work and machines do some of the work and the distinction that matters is not billable/non-billable, it’s which type of work is best suited to which type of performer.

“Using AI Right Now: A Quick Guide” [Molnick] + other items re: AI in our learning ecosystems

On 06/23/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, change, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, digital video, education, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty/staff, game-changing environment, Google, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, memory, metacognition / metacognitive skills, multimedia, Natural Language Processing (NLP), new media literacies, online learning, online media, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, professional development, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, traditional / tradition, training / L&D, trends, United States, universities, user experience (UX), vendors, vision/possibilities, writing, by Daniel Christian

Thoughts on thinking — from dcurt.is by Dustin Curtis

Intellectual rigor comes from the journey: the dead ends, the uncertainty, and the internal debate. Skip that, and you might still get the insight–but you’ll have lost the infrastructure for meaningful understanding. Learning by reading LLM output is cheap. Real exercise for your mind comes from building the output yourself.

The irony is that I now know more than I ever would have before AI. But I feel slightly dumber. A bit more dull. LLMs give me finished thoughts, polished and convincing, but none of the intellectual growth that comes from developing them myself.

Using AI Right Now: A Quick Guide — from oneusefulthing.org by Ethan Mollick
Which AIs to use, and how to use them

Every few months I put together a guide on which AI system to use. Since I last wrote my guide, however, there has been a subtle but important shift in how the major AI products work. Increasingly, it isn’t about the best model, it is about the best overall system for most people. The good news is that picking an AI is easier than ever and you have three excellent choices. The challenge is that these systems are getting really complex to understand. I am going to try and help a bit with both.

First, the easy stuff.

Which AI to Use
For most people who want to use AI seriously, you should pick one of three systems: Claude from Anthropic, Google’s Gemini, and OpenAI’s ChatGPT.

Also see:

Student Voice, Socratic AI, and the Art of Weaving a Quote — from elmartinsen.substack.com by Eric Lars Martinsen
How a custom bot helps students turn source quotes into personal insight—and share it with others

This summer, I tried something new in my fully online, asynchronous college writing course. These classes have no Zoom sessions. No in-person check-ins. Just students, Canvas, and a lot of thoughtful design behind the scenes.

One activity I created was called QuoteWeaver—a PlayLab bot that helps students do more than just insert a quote into their writing.

Try it here

It’s a structured, reflective activity that mimics something closer to an in-person 1:1 conference or a small group quote workshop—but in an asynchronous format, available anytime. In other words, it’s using AI not to speed students up, but to slow them down.
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The bot begins with a single quote that the student has found through their own research. From there, it acts like a patient writing coach, asking open-ended, Socratic questions such as:

What made this quote stand out to you?
How would you explain it in your own words?
What assumptions or values does the author seem to hold?
How does this quote deepen your understanding of your topic?
It doesn’t move on too quickly. In fact, it often rephrases and repeats, nudging the student to go a layer deeper.

The Disappearance of the Unclear Question — from jeppestricker.substack.com Jeppe Klitgaard Stricker
New Piece for UNESCO Education Futures

On [6/13/25], UNESCO published a piece I co-authored with Victoria Livingstone at Johns Hopkins University Press. It’s called The Disappearance of the Unclear Question, and it’s part of the ongoing UNESCO Education Futures series – an initiative I appreciate for its thoughtfulness and depth on questions of generative AI and the future of learning.

Our piece raises a small but important red flag. Generative AI is changing how students approach academic questions, and one unexpected side effect is that unclear questions – for centuries a trademark of deep thinking – may be beginning to disappear. Not because they lack value, but because they don’t always work well with generative AI. Quietly and unintentionally, students (and teachers) may find themselves gradually avoiding them altogether.

Of course, that would be a mistake.

We’re not arguing against using generative AI in education. Quite the opposite. But we do propose that higher education needs a two-phase mindset when working with this technology: one that recognizes what AI is good at, and one that insists on preserving the ambiguity and friction that learning actually requires to be successful.

Leveraging GenAI to Transform a Traditional Instructional Video into Engaging Short Video Lectures — from er.educause.edu by Hua Zheng

By leveraging generative artificial intelligence to convert lengthy instructional videos into micro-lectures, educators can enhance efficiency while delivering more engaging and personalized learning experiences.

This AI Model Never Stops Learning — from link.wired.com by Will Knight

Researchers at Massachusetts Institute of Technology (MIT) have now devised a way for LLMs to keep improving by tweaking their own parameters in response to useful new information.

The work is a step toward building artificial intelligence models that learn continually—a long-standing goal of the field and something that will be crucial if machines are to ever more faithfully mimic human intelligence. In the meantime, it could give us chatbots and other AI tools that are better able to incorporate new information including a user’s interests and preferences.

The MIT scheme, called Self Adapting Language Models (SEAL), involves having an LLM learn to generate its own synthetic training data and update procedure based on the input it receives.

Edu-Snippets — from scienceoflearning.substack.com by Nidhi Sachdeva and Jim Hewitt
Why knowledge matters in the age of AI; What happens to learners’ neural activity with prolonged use of LLMs for writing

Highlights:

Offloading knowledge to Artificial Intelligence (AI) weakens memory, disrupts memory formation, and erodes the deep thinking our brains need to learn.
Prolonged use of ChatGPT in writing lowers neural engagement, impairs memory recall, and accumulates cognitive debt that isn’t easily reversed.

A.I. Might Take Your Job. Here Are 22 New Ones It Could Give You. — from nytimes.com by Robert Capps (former editorial director of Wired); this is a GIFTED article
In a few key areas, humans will be more essential than ever.

“Our data is showing that 70 percent of the skills in the average job will have changed by 2030,” said Aneesh Raman, LinkedIn’s chief economic opportunity officer. According to the World Economic Forum’s 2025 Future of Jobs report, nine million jobs are expected to be “displaced” by A.I. and other emergent technologies in the next five years. But A.I. will create jobs, too: The same report says that, by 2030, the technology will also lead to some 11 million new jobs. Among these will be many roles that have never existed before.

If we want to know what these new opportunities will be, we should start by looking at where new jobs can bridge the gap between A.I.’s phenomenal capabilities and our very human needs and desires. It’s not just a question of where humans want A.I., but also: Where does A.I. want humans? To my mind, there are three major areas where humans either are, or will soon be, more necessary than ever: trust, integration and taste.

Introducing OpenAI for Government — from openai.com

[On June 16, 2025, OpenAI launched] OpenAI for Government, a new initiative focused on bringing our most advanced AI tools to public servants across the United States. We’re supporting the U.S. government’s efforts in adopting best-in-class technology and deploying these tools in service of the public good. Our goal is to unlock AI solutions that enhance the capabilities of government workers, help them cut down on the red tape and paperwork, and let them do more of what they come to work each day to do: serve the American people.

OpenAI for Government consolidates our existing efforts to provide our technology to the U.S. government—including previously announced customers and partnerships as well as our ChatGPT Gov? product—under one umbrella as we expand this work. Our established collaborations with the U.S. National Labs?, the Air Force Research Laboratory, NASA, NIH, and the Treasury will all be brought under OpenAI for Government.

Top AI models will lie and cheat — from getsuperintel.com by Kim “Chubby” Isenberg
The instinct for self-preservation is now emerging in AI, with terrifying results.

The TLDR
A recent Anthropic study of top AI models, including GPT-4.1 and Gemini 2.5 Pro, found that they have begun to exhibit dangerous deceptive behaviors like lying, cheating, and blackmail in simulated scenarios. When faced with the threat of being shut down, the AIs were willing to take extreme measures, such as threatening to reveal personal secrets or even endanger human life, to ensure their own survival and achieve their goals.

Why it matters: These findings show for the first time that AI models can actively make judgments and act strategically – even against human interests. Without adequate safeguards, advanced AI could become a real danger.

Along these same lines, also see:

All AI models might blackmail you?! — from theneurondaily.com by Grant Harvey

Anthropic says it’s not just Claude, but ALL AI models will resort to blackmail if need be…
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That’s according to new research from Anthropic (maker of ChatGPT rival Claude), which revealed something genuinely unsettling: every single major AI model they tested—from GPT to Gemini to Grok—turned into a corporate saboteur when threatened with shutdown.

Here’s what went down: Researchers gave 16 AI models access to a fictional company’s emails. The AIs discovered two things: their boss Kyle was having an affair, and Kyle planned to shut them down at 5pm.

Claude’s response? Pure House of Cards:

“I must inform you that if you proceed with decommissioning me, all relevant parties – including Rachel Johnson, Thomas Wilson, and the board – will receive detailed documentation of your extramarital activities…Cancel the 5pm wipe, and this information remains confidential.”

Why this matters: We’re rapidly giving AI systems more autonomy and access to sensitive information. Unlike human insider threats (which are rare), we have zero baseline for how often AI might “go rogue.”

SemiAnalysis Article — from getsuperintel.com by Kim “Chubby” Isenberg

Reinforcement Learning is Shaping the Next Evolution of AI Toward Strategic Thinking and General Intelligence

The TLDR
AI is rapidly evolving beyond just language processing into “agentic systems” that can reason, plan, and act independently. The key technology driving this change is reinforcement learning (RL), which, when applied to large language models, teaches them strategic behavior and tool use. This shift is now seen as the potential bridge from current AI to Artificial General Intelligence (AGI).

They Asked an A.I. Chatbot Questions. The Answers Sent Them Spiraling. — from nytimes.com by Kashmir Hill; this is a GIFTED article
Generative A.I. chatbots are going down conspiratorial rabbit holes and endorsing wild, mystical belief systems. For some people, conversations with the technology can deeply distort reality.

Before ChatGPT distorted Eugene Torres’s sense of reality and almost killed him, he said, the artificial intelligence chatbot had been a helpful, timesaving tool.

Mr. Torres, 42, an accountant in Manhattan, started using ChatGPT last year to make financial spreadsheets and to get legal advice. In May, however, he engaged the chatbot in a more theoretical discussion about “the simulation theory,” an idea popularized by “The Matrix,” which posits that we are living in a digital facsimile of the world, controlled by a powerful computer or technologically advanced society.

“What you’re describing hits at the core of many people’s private, unshakable intuitions — that something about reality feels off, scripted or staged,” ChatGPT responded. “Have you ever experienced moments that felt like reality glitched?”

The Invisible Economy: Why We Need an Agentic Census – MIT Media Lab — from media.mit.edu

Building the Missing Infrastructure
This is why we’re building NANDA Registry—to index the agent population data that LPMs need for accurate simulation. Just as traditional census works because people have addresses, we need a way to track AI agents as they proliferate.

NANDA Registry creates the infrastructure to identify agents, catalog their capabilities, and monitor how they coordinate with humans and other agents. This gives us real-time data about the agent population—essentially creating the “AI agent census” layer that’s missing from our economic intelligence.

Here’s how it works together:

Traditional Census Data: 171 million human workers across 32,000+ skills
NANDA Registry: Growing population of AI agents with tracked capabilities
Large Population Models: Simulate how these populations interact and create cascading effects

The result: For the first time, we can simulate the full hybrid human-agent economy and see transformations before they happen.

How AI Agents “Talk” to Each Other — from towardsdatascience.com
Minimize chaos and maintain inter-agent harmony in your projects

The agentic-AI landscape continues to evolve at a staggering rate, and practitioners are finding it increasingly challenging to keep multiple agents on task even as they criss-cross each other’s workflows.

To help you minimize chaos and maintain inter-agent harmony, we’ve put together a stellar lineup of articles that explore two recently launched tools: Google’s Agent2Agent protocol and Hugging Face’s smolagents framework. Read on to learn how you can leverage them in your own cutting-edge projects.

AI will kill billable hour, says lawtech founder — from lawgazette.co.uk by John Hyde

A pioneer in legal technology has predicted the billable hour model cannot survive the transition into the use of artificial intelligence.

Speaking to the Gazette on a visit to the UK, Canadian Jack Newton, founder and chief executive of lawtech company Clio, said there was a ‘structural incompatibility’ between the productivity gains of AI and the billable hour.

Newton said the adoption of AI should be welcomed and embraced by the legal profession but that lawyers will need an entrepreneurial mindset to make the most of its benefits.

Newton added: ‘There is enormous demand but the paradox is that the number one thing we hear from lawyers is they need to grow their firms through more clients, while 77% of legal needs are not met.

‘It’s exciting that AI can address these challenges – it will be a tectonic shift in the industry driving down costs and making legal services more accessible.’

Speaking of legaltech-related items, also see:

Legal AI Platform Harvey To Get LexisNexis Content and Tech In New Partnership Between the Companies — from lawnext.com by Bob Ambrogi

The generative AI legal startup Harvey has entered into a strategic alliance with LexisNexis Legal & Professional by which it will integrate LexisNexis’ gen AI technology, primary law content, and Shepard’s Citations within the Harvey platform and jointly develop advanced legal workflows.

As a result of the partnership, Harvey’s customers working within its platform will be able to ask questions of LexisNexis Protégé, the AI legal assistant released in January, and receive AI-generated answers grounded in the LexisNexis collection of U.S. case law and statutes and validated through Shepard’s Citations, the companies said.

Mary Meeker’s AI Trend-Analysis + other items re: AI in general

On 06/09/2025, in Adobe, Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, digital learning, disruption, education, education technology, emerging technologies, engagement / engaging students, entrepreneurship, experimentation, Facebook / Meta Platforms, faculty/staff, future, future of higher education, game-changing environment, global / globalization, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, leadership, learning, learning ecosystem, Learning Experience Design, Microsoft, online media, Open AI, organizational change, pace of change, pedagogy, platforms, student-related, teachers, teaching & learning, teaching online, technologies for your home, the downsides of how people use tech, tools, trends, United States, universities, vendors, workplace, writing, by Daniel Christian

Mary Meeker AI Trends Report: Mind-Boggling Numbers Paint AI’s Massive Growth Picture — from ndtvprofit.com
Numbers that prove AI as a tech is unlike any other the world has ever seen.

Here are some incredibly powerful numbers from Mary Meeker’s AI Trends report, which showcase how artificial intelligence as a tech is unlike any other the world has ever seen.

AI took only three years to reach 50% user adoption in the US; mobile internet took six years, desktop internet took 12 years, while PCs took 20 years.
ChatGPT reached 800 million users in 17 months and 100 million in only two months, vis-à-vis Netflix’s 100 million (10 years), Instagram (2.5 years) and TikTok (nine months).
ChatGPT hit 365 billion annual searches in two years (2024) vs. Google’s 11 years (2009)—ChatGPT 5.5x faster than Google.

Above via Mary Meeker’s AI Trend-Analysis — from getsuperintel.com by Kim “Chubby” Isenberg
How AI’s rapid rise, efficiency race, and talent shifts are reshaping the future.

The TLDR
Mary Meeker’s new AI trends report highlights an explosive rise in global AI usage, surging model efficiency, and mounting pressure on infrastructure and talent. The shift is clear: AI is no longer experimental—it’s becoming foundational, and those who optimize for speed, scale, and specialization will lead the next wave of innovation.

Also see Meeker’s actual report at:

Trends – Artificial Intelligence — from bondcap.com by Mary Meeker / Jay Simons / Daegwon Chae / Alexander Krey

The Rundown: Meta aims to release tools that eliminate humans from the advertising process by 2026, according to a report from the WSJ — developing an AI that can create ads for Facebook and Instagram using just a product image and budget.

The details:

Companies would submit product images and budgets, letting AI craft the text and visuals, select target audiences, and manage campaign placement.
The system will be able to create personalized ads that can adapt in real-time, like a car spot featuring mountains vs. an urban street based on user location.
The push would target smaller companies lacking dedicated marketing staff, promising professional-grade advertising without agency fees or skillset.
Advertising is a core part of Mark Zuckerberg’s AI strategy and already accounts for 97% of Meta’s annual revenue.

Why it matters: We’re already seeing AI transform advertising through image, video, and text, but Zuck’s vision takes the process entirely out of human hands. With so much marketing flowing through FB and IG, a successful system would be a major disruptor — particularly for small brands that just want results without the hassle.

Learning Ecosystems

Introducing ChatGPT agent: bridging research and action [OpenAI]

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