experimentation

“OpenAI wants to pair online courses with chatbots” [Wiggers] + other items re: AI in our learning ecosytems

On 12/07/2024, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, business, career development, change, changing business models, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, experimentation, faculty, future, future of higher education, game-changing environment, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, new business models, online learning, Open AI, platforms, productivity / tips and tricks, professional development, research, skills, society, sociology, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, workplace, writing, youth, by Daniel Christian

What Students Are Saying About Teachers Using A.I. to Grade — from nytimes.com by ; via Claire Zau
Teenagers and educators weigh in on a recent question from The Ethicist.

Is it unethical for teachers to use artificial intelligence to grade papers if they have forbidden their students from using it for their assignments?

That was the question a teacher asked Kwame Anthony Appiah in a recent edition of The Ethicist. We posed it to students to get their take on the debate, and asked them their thoughts on teachers using A.I. in general.

While our Student Opinion questions are usually reserved for teenagers, we also heard from a few educators about how they are — or aren’t — using A.I. in the classroom. We’ve included some of their answers, as well.

OpenAI wants to pair online courses with chatbots — from techcrunch.com by Kyle Wiggers; via James DeVaney on LinkedIn

If OpenAI has its way, the next online course you take might have a chatbot component.

Speaking at a fireside on Monday hosted by Coeus Collective, Siya Raj Purohit, a member of OpenAI’s go-to-market team for education, said that OpenAI might explore ways to let e-learning instructors create custom “GPTs” that tie into online curriculums.

“What I’m hoping is going to happen is that professors are going to create custom GPTs for the public and let people engage with content in a lifelong manner,” Purohit said. “It’s not part of the current work that we’re doing, but it’s definitely on the roadmap.”

Learning About Google Learn About: What Educators Need To Know — from techlearning.com by Ray Bendici
Google’s experimental Learn About platform is designed to create an AI-guided learning experience

Google Learn About is a new experimental AI-driven platform available that provides digestible and in-depth knowledge about various topics, but showcases it all in an educational context. Described by Google as a “conversational learning companion,” it is essentially a Wikipedia-style chatbot/search engine, and then some.

In addition to having a variety of already-created topics and leading questions (in areas such as history, arts, culture, biology, and physics) the tool allows you to enter prompts using either text or an image. It then provides a general overview/answer, and then suggests additional questions, topics, and more to explore in regard to the initial subject.

The idea is for student use is that the AI can help guide a deeper learning process rather than just provide static answers.

What OpenAI’s PD for Teachers Does—and Doesn’t—Do — from edweek.org by Olina Banerji
What’s the first thing that teachers dipping their toes into generative artificial intelligence should do?

They should start with the basics, according to OpenAI, the creator of ChatGPT and one of the world’s most prominent artificial intelligence research companies. Last month, the company launched an hour-long, self-paced online course for K-12 teachers about the definition, use, and harms of generative AI in the classroom. It was launched in collaboration with Common Sense Media, a national nonprofit that rates and reviews a wide range of digital content for its age appropriateness.

…the above article links to:

ChatGPT Foundations for K–12 Educators — from commonsense.org

This course introduces you to the basics of artificial intelligence, generative AI, ChatGPT, and how to use ChatGPT safely and effectively. From decoding the jargon to responsible use, this course will help you level up your understanding of AI and ChatGPT so that you can use tools like this safely and with a clear purpose.

Learning outcomes:

Understand what ChatGPT is and how it works.
Demonstrate ways to use ChatGPT to support your teaching practices.
Implement best practices for applying responsible AI principles in a school setting.

Takeaways From Google’s Learning in the AI Era Event — from edtechinsiders.substack.com by Sarah Morin, Alex Sarlin, and Ben Kornell
Highlights from Our Day at Google + Behind-the-Scenes Interviews Coming Soon!

NotebookLM: The Start of an AI Operating System
Google is Serious About AI and Learning
Google’s LearnLM Now Available in AI Studio
Collaboration is King
If You Give a Teacher a Ferrari

Rapid Responses to AI — from the-job.beehiiv.com by Paul Fain
Top experts call for better data and more short-term training as tech transforms jobs.

AI could displace middle-skill workers and widen the wealth gap, says landmark study, which calls for better data and more investment in continuing education to help workers make career pivots.
…
Ensuring That AI Helps Workers
Artificial intelligence has emerged as a general purpose technology with sweeping implications for the workforce and education. While it’s impossible to precisely predict the scope and timing of looming changes to the labor market, the U.S. should build its capacity to rapidly detect and respond to AI developments.
That’s the big-ticket framing of a broad new report from the National Academies of Sciences, Engineering, and Medicine. Congress requested the study, tapping an all-star committee of experts to assess the current and future impact of AI on the workforce.

“In contemplating what the future holds, one must approach predictions with humility,” the study says…

“AI could accelerate occupational polarization,” the committee said, “by automating more nonroutine tasks and increasing the demand for elite expertise while displacing middle-skill workers.”
…
The Kicker: “The education and workforce ecosystem has a responsibility to be intentional with how we value humans in an AI-powered world and design jobs and systems around that,” says Hsieh.

Why We Undervalue Ideas and Overvalue Writing — from aiczar.blogspot.com by Alexander “Sasha” Sidorkin

A student submits a paper that fails to impress stylistically yet approaches a worn topic from an angle no one has tried before. The grade lands at B minus, and the student learns to be less original next time. This pattern reveals a deep bias in higher education: ideas lose to writing every time.

This bias carries serious equity implications. Students from disadvantaged backgrounds, including first-generation college students, English language learners, and those from under-resourced schools, often arrive with rich intellectual perspectives but struggle with academic writing conventions. Their ideas – shaped by unique life experiences and cultural viewpoints – get buried under red ink marking grammatical errors and awkward transitions. We systematically undervalue their intellectual contributions simply because they do not arrive in standard academic packaging.

Google Scholar’s New AI Outline Tool Explained By Its Founder — from techlearning.com by Erik Ofgang
Google Scholar PDF reader uses Gemini AI to read research papers. The AI model creates direct links to the paper’s citations and a digital outline that summarizes the different sections of the paper.

Google Scholar has entered the AI revolution. Google Scholar PDF reader now utilizes generative AI powered by Google’s Gemini AI tool to create interactive outlines of research papers and provide direct links to sources within the paper. This is designed to make reading the relevant parts of the research paper more efficient, says Anurag Acharya, who co-founded Google Scholar on November 18, 2004, twenty years ago last month.

The Four Most Powerful AI Use Cases in Instructional Design Right Now — from drphilippahardman.substack.com by Dr. Philippa Hardman
Insights from ~300 instructional designers who have taken my AI & Learning Design bootcamp this year

AI-Powered Analysis: Creating Detailed Learner Personas…
AI-Powered Design: Optimising Instructional Strategies…
AI-Powered Development & Implementation: Quality Assurance…
AI-Powered Evaluation: Predictive Impact Assessment…

How Are New AI Tools Changing ‘Learning Analytics’? — from edsurge.com by Jeffrey R. Young
For a field that has been working to learn from the data trails students leave in online systems, generative AI brings new promises — and new challenges.

In other words, with just a few simple instructions to ChatGPT, the chatbot can classify vast amounts of student work and turn it into numbers that educators can quickly analyze.

Findings from learning analytics research is also being used to help train new generative AI-powered tutoring systems.
…
Another big application is in assessment, says Pardos, the Berkeley professor. Specifically, new AI tools can be used to improve how educators measure and grade a student’s progress through course materials. The hope is that new AI tools will allow for replacing many multiple-choice exercises in online textbooks with fill-in-the-blank or essay questions.

VLOG: Learning in Medical School [The Learning Scientists]

On 12/07/2024, in Emotion, experimentation, faculty, health, higher education, instructional design, learning, learning ecosystem, Learning Experience Design, memory, productivity / tips and tricks, student-related, teaching & learning, United States, universities, vendors, by Daniel Christian

VLOG: Learning in Medical School — from learningscientists.org by The Learning Scientists

NOTE:

This vlog is for anyone in medical school, interested in medical school, or just curious about what learning is like in medical school!

In this vlog Althea and Cindy talk about their work with medical student learners. They discuss common learning challenges in medical school, efficient learning strategies, learning in the context of attentional disorders and anxiety, and what it means to prepare future healers.

Closing the digital use divide with active and engaging learning [Ascione]

On 12/04/2024, in active learning, Artificial Intelligence/Agents/LLMs/and Related, collaboration, communications, computer science, content development, aggregation, repositories, creativity, curriculum, data related items, education, education technology, educational games / serious games, engagement / engaging students, experimentation, face-to-face, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, learning preferences, multimedia, new media literacies, personalized/customized learning, programming, simulations, skills, student teaching/teacher education, student-related, teachers, tools, United States, vendors, Virtual Reality (VR) / worlds / learning, vision/possibilities, XR - extended reality, youth, by Daniel Christian

Closing the digital use divide with active and engaging learning — from eschoolnews.com by Laura Ascione
Students offered insight into how to use active learning, with digital tools, to boost their engagement

When it comes to classroom edtech use, digital tools have a drastically different impact when they are used actively instead of passively–a critical difference examined in the 2023-2024 Speak Up Research by Project Tomorrow.

Students also outlined their ideal active learning technologies:

Collaboration tools to support projects
Student-teacher communication tools
Online databases for self-directed research
Multi-media tools for creating new content
Online and digital games
AI tools to support personalized learning
Coding and computer programming resources
Online animations, simulations, and virtual labs
Virtual reality equipment and content

(Excerpt from the 12/4/24 edition)

Robot “Jailbreaks”
In the year or so since large language models hit the big time, researchers have demonstrated numerous ways of tricking them into producing problematic outputs including hateful jokes, malicious code, phishing emails, and the personal information of users. It turns out that misbehavior can take place in the physical world, too: LLM-powered robots can easily be hacked so that they behave in potentially dangerous ways.

Researchers from the University of Pennsylvania were able to persuade a simulated self-driving car to ignore stop signs and even drive off a bridge, get a wheeled robot to find the best place to detonate a bomb, and force a four-legged robot to spy on people and enter restricted areas.

“We view our attack not just as an attack on robots,” says George Pappas, head of a research lab at the University of Pennsylvania who helped unleash the rebellious robots. “Any time you connect LLMs and foundation models to the physical world, you actually can convert harmful text into harmful actions.”
…
The robot “jailbreaks” highlight a broader risk that is likely to grow as AI models become increasingly used as a way for humans to interact with physical systems, or to enable AI agents autonomously on computers, say the researchers involved.

Virtual lab powered by ‘AI scientists’ super-charges biomedical research — from nature.com by Helena Kudiabor
Could human-AI collaborations be the future of interdisciplinary studies?

In an effort to automate scientific discovery using artificial intelligence (AI), researchers have created a virtual laboratory that combines several ‘AI scientists’ — large language models with defined scientific roles — that can collaborate to achieve goals set by human researchers.

The system, described in a preprint posted on bioRxiv last month¹, was able to design antibody fragments called nanobodies that can bind to the virus that causes COVID-19, proposing nearly 100 of these structures in a fraction of the time it would take an all-human research group.

Can AI agents accelerate AI implementation for CIOs? — from intelligentcio.com by Arun Shankar

By embracing an agent-first approach, every CIO can redefine their business operations. AI agents are now the number one choice for CIOs as they come pre-built and can generate responses that are consistent with a company’s brand using trusted business data, explains Thierry Nicault at Salesforce Middle.

AI Turns Photos Into 3D Real World — from theaivalley.com by Barsee

Here’s what you need to know:

The system generates full 3D environments that expand beyond what’s visible in the original image, allowing users to explore new perspectives.
Users can freely navigate and view the generated space with standard keyboard and mouse controls, similar to browsing a website.
It includes real-time camera effects like depth-of-field and dolly zoom, as well as interactive lighting and animation sliders to tweak scenes.
The system works with both photos and AI-generated images, enabling creators to integrate it with text-to-image tools or even famous works of art.

Why it matters:
This technology opens up exciting possibilities for industries like gaming, film, and virtual experiences. Soon, creating fully immersive worlds could be as simple as generating a static image.

Also related, see:

World Labs’ AI can generate interactive 3D scenes from a single photo — from techcrunch.com by Kyle Wiggers

From World Labs

Today we’re sharing our first step towards spatial intelligence: an AI system that generates 3D worlds from a single image. This lets you step into any image and explore it in 3D.

Most GenAI tools make 2D content like images or videos. Generating in 3D instead improves control and consistency. This will change how we make movies, games, simulators, and other digital manifestations of our physical world.

In this post you’ll explore our generated worlds, rendered live in your browser. You’ll also experience different camera effects, 3D effects, and dive into classic paintings. Finally, you’ll see how creators are already building with our models.

Addendum on 12/5/24:

ChatGPT turns two: how has it impacted markets? — from moneyweek.com
Two years on from ChatGPT’s explosive launch into the public sphere, we assess the impact that it has had on stock markets and the world of technology

What Happens When ‘Play’ Is Left Out of the School Curriculum — from edsurge.com by Fatema Elbakoury
When two birds flew into my classroom, I realized how much teachers lose when we don’t trust students to play.

Due to the rigidity of curriculum, standardized tests and the controlling nature of compulsory education, playfulness and unstructured time are seen as detrimental to a student’s learning. But what is learning and why is play seen as so antithetical to teaching? What if we centered playfulness and unstructured time in our classrooms, even when it has nothing to do with the curriculum? Part of learning is acquiring knowledge through experience. If play is an experience it, too, can result in the acquisition of knowledge.

Campus webinar: The art of bringing creativity and fun into the classroom — from Times Higher Education

In our latest webinar, we spoke to three experts from Campus+ partner across the UK to discuss creative and fun ways to get students engaged, both online and in the classroom.

Gary Burnett from Loughborough University, Simon Brownhill from the University of Bristol and Kelly Edmunds from the University of East Anglia talked to us about:

Creative and fun ways to get students engaged, in-person and online
Tapping into students’ creativity for better learning outcomes
Creating a culture of creativity and experimentation
Breaking down disciplinary boundaries for learning and collaboration
Creative ways to bring AI into classroom activities and assignments
Play as a powerful teaching tool

DC: This is a great posting! “AI Tutors: Hype or Hope for Education?” [Bailey & Warner]

On 12/04/2024, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, future, game-changing environment, Google, human-computer interaction (HCI), 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 preferences, mathematics, multimedia, new media literacies, Open AI, personalized/customized learning, relationships, science, skills, student-related, teachers, the downsides of how people use tech, United States, vendors, vision/possibilities, writing, by Daniel Christian

AI Tutors: Hype or Hope for Education? — from educationnext.org by John Bailey and John Warner
In a new book, Sal Khan touts the potential of artificial intelligence to address lagging student achievement. Our authors weigh in.

In Salman Khan’s new book, Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing) (Viking, 2024), the Khan Academy founder predicts that AI will transform education by providing every student with a virtual personalized tutor at an affordable cost. Is Khan right? Is radically improved achievement for all students within reach at last? If so, what sorts of changes should we expect to see, and when? If not, what will hold back the AI revolution that Khan foresees? John Bailey, a visiting fellow at the American Enterprise Institute, endorses Khan’s vision and explains the profound impact that AI technology is already making in education. John Warner, a columnist for the Chicago Tribune and former editor for McSweeney’s Internet Tendency, makes the case that all the hype about AI tutoring is, as Macbeth quips, full of sound and fury, signifying nothing.

Two items re: AI in our learning ecosystems

On 11/27/2024, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, future, future of higher education, game-changing environment, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, platforms, productivity / tips and tricks, research, skills, student-related, teaching & learning, tools, training / L&D, United States, universities, vendors, by Daniel Christian

From DSC:
Notebook LM continues to make waves…

2024: The State of Generative AI in the Enterprise — from menlovc.com (Menlo Ventures)
The enterprise AI landscape is being rewritten in real time. As pilots give way to production, we surveyed 600 U.S. enterprise IT decision-makers to reveal the emerging winners and losers.

This spike in spending reflects a wave of organizational optimism; 72% of decision-makers anticipate broader adoption of generative AI tools in the near future. This confidence isn’t just speculative—generative AI tools are already deeply embedded in the daily work of professionals, from programmers to healthcare providers.

Despite this positive outlook and increasing investment, many decision-makers are still figuring out what will and won’t work for their businesses. More than a third of our survey respondents do not have a clear vision for how generative AI will be implemented across their organizations. This doesn’t mean they’re investing without direction; it simply underscores that we’re still in the early stages of a large-scale transformation. Enterprise leaders are just beginning to grasp the profound impact generative AI will have on their organizations.

Business spending on AI surged 500% this year to $13.8 billion, says Menlo Ventures — from cnbc.com by Hayden Field

Key Points

Business spending on generative AI surged 500% this year, hitting $13.8 billion — up from just $2.3 billion in 2023, according to data from Menlo Ventures released Wednesday.
OpenAI ceded market share in enterprise AI, declining from 50% to 34%, per the report.
Amazon-backed Anthropic doubled its market share from 12% to 24%.

Microsoft quietly assembles the largest AI agent ecosystem—and no one else is close — from venturebeat.com by Matt Marshall

Microsoft has quietly built the largest enterprise AI agent ecosystem, with over 100,000 organizations creating or editing AI agents through its Copilot Studio since launch – a milestone that positions the company ahead in one of enterprise tech’s most closely watched and exciting segments.
…
The rapid adoption comes as Microsoft significantly expands its agent capabilities. At its Ignite conference [that started on 11/19/24], the company announced it will allow enterprises to use any of the 1,800 large language models (LLMs) in the Azure catalog within these agents – a significant move beyond its exclusive reliance on OpenAI’s models. The company also unveiled autonomous agents that can work independently, detecting events and orchestrating complex workflows with minimal human oversight.

Now Hear This: World’s Most Flexible Sound Machine Debuts — from
Using text and audio as inputs, a new generative AI model from NVIDIA can create any combination of music, voices and sounds.

Along these lines, also see:

Nvidia unveils AI model for music, audio that can modify voices, generate new sounds — from seekingalpha.com

AI Agents Versus Human Agency: 4 Ways To Navigate Our AI-Driven World — from forbes.com by Cornelia C. Walther

To understand the implications of AI agents, it’s useful to clarify the distinctions between AI, generative AI, and AI agents and explore the opportunities and risks they present to our autonomy, relationships, and decision-making.
…
AI Agents: These are specialized applications of AI designed to perform tasks or simulate interactions. AI agents can be categorized into:

- Tool Agents…
- Simulation Agents..

While generative AI creates outputs from prompts, AI agents use AI to act with intention, whether to assist (tool agents) or emulate (simulation agents). The latter’s ability to mirror human thought and action offers fascinating possibilities — and raises significant risks.

For a true meritocracy, education must not be one-size-fits-all [Chung]

On 11/27/2024, in career development, curriculum, Daniel S. Christian, education, education reform, Europe, experimentation, K-12 related, leadership, learning ecosystem, more voice more choice more control, skills, strategy, teachers, United States, vision/possibilities, vocational / trades, youth, by Daniel Christian

For a true meritocracy, education must not be one-size-fits-all — from edsource.org by Eric Chung

What we can do is stop deciding who is educated, intelligent and successful based on only one type of student. Instead, we should recognize the value of all students, and offer more mainstream career and technical opportunities across K-12 education.

From DSC:
Note the power of CHOICE in this next excerpt:

There is another possibility. Consider Finland, which in the 1970s switched from the German model to one that teaches a combination of academic and technical subjects until age 16, when students choose a track. The vocational path for students interested in highly -skilled trades includes carpentry and culinary arts, but it also offers applied sciences, health care, and social services, which in the United States would require attending traditional academic universities.

.
Learners need: More voice. More choice. More control. -- this image was created by Daniel Christian

2024-11-22: The Race to the TopDario Amodei on AGI, Risks, and the Future of Anthropic — from emergentbehavior.co by Prakash (Ate-a-Pi)

Risks on the Horizon: ASL Levels
The two key risks Dario is concerned about are:

a) cyber, bio, radiological, nuclear (CBRN)
b) model autonomy

These risks are captured in Anthropic’s framework for understanding AI Safety Levels (ASL):

1. ASL-1: Narrow-task AI like Deep Blue (no autonomy, minimal risk).
2. ASL-2: Current systems like ChatGPT/Claude, which lack autonomy and don’t pose significant risks beyond information already accessible via search engines.
3. ASL-3: Agents arriving soon (potentially next year) that can meaningfully assist non-state actors in dangerous activities like cyber or CBRN (chemical, biological, radiological, nuclear) attacks. Security and filtering are critical at this stage to prevent misuse.
4. ASL-4: AI smart enough to evade detection, deceive testers, and assist state actors with dangerous projects. AI will be strong enough that you would want to use the model to do anything dangerous. Mechanistic interpretability becomes crucial for verifying AI behavior.
5. ASL-5: AGI surpassing human intelligence in all domains, posing unprecedented challenges.

Anthropic’s if/then framework ensures proactive responses: if a model demonstrates danger, the team clamps down hard, enforcing strict controls.

Should You Still Learn to Code in an A.I. World? — from nytimes.com by
Coding boot camps once looked like the golden ticket to an economically secure future. But as that promise fades, what should you do? Keep learning, until further notice.

Compared with five years ago, the number of active job postings for software developers has dropped 56 percent, according to data compiled by CompTIA. For inexperienced developers, the plunge is an even worse 67 percent.
“I would say this is the worst environment for entry-level jobs in tech, period, that I’ve seen in 25 years,” said Venky Ganesan, a partner at the venture capital firm Menlo Ventures.

For years, the career advice from everyone who mattered — the Apple chief executive Tim Cook, your mother — was “learn to code.” It felt like an immutable equation: Coding skills + hard work = job.

Now the math doesn’t look so simple.

Also see:

AI builds apps in 2 mins flat — where the Neuron mentions this excerpt about Lovable:

There’s a new coding startup in town, and it just MIGHT have everybody else shaking in their boots (we’ll qualify that in a sec, don’t worry).

It’s called Lovable, the “world’s first AI fullstack engineer.”
…
Lovable does all of that by itself. Tell it what you want to build in plain English, and it creates everything you need. Want users to be able to log in? One click. Need to store data? One click. Want to accept payments? You get the idea.

Early users are backing up these claims. One person even launched a startup that made Product Hunt’s top 10 using just Lovable.

As for us, we made a Wordle clone in 2 minutes with one prompt. Only edit needed? More words in the dictionary. It’s like, really easy y’all.

When to chat with AI (and when to let it work) — from aiwithallie.beehiiv.com by Allie K. Miller

Re: some ideas on how to use Notebook LM:

Turn your company’s annual report into an engaging podcast
Create an interactive FAQ for your product manual
Generate a timeline of your industry’s history from multiple sources
Produce a study guide for your online course content
Develop a Q&A system for your company’s knowledge base
Synthesize research papers into digestible summaries
Create an executive content briefing from multiple competitor blog posts
Generate a podcast discussing the key points of a long-form research paper

Introducing conversation practice: AI-powered simulations to build soft skills — from codesignal.com by Albert Sahakyan

From DSC:
I have to admit I’m a bit suspicious here, as the “conversation practice” product seems a bit too scripted at times, but I post it because the idea of using AI to practice soft skills development makes a great deal of sense:

This is mind-blowing!

NVIDIA has introduced Edify 3D, a 3D AI generator that lets us create high-quality 3D scenes using just a simple prompt. And all the assets are fully editable!

This is going to revolutionise the way we create!

5 Examples: pic.twitter.com/5yWlvL1cWD

— el.cine (@EHuanglu) November 24, 2024

Denmark’s Gefion: The AI supercomputer that puts society first [Nest]

On 11/21/2024, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, collaboration, computer science, corporate / business world, emerging technologies, Europe, experimentation, future, game-changing environment, generational differences, NVIDIA, platforms, society, by Daniel Christian

Denmark’s Gefion: The AI supercomputer that puts society first — from blog.aiport.tech by Daniel Nest
Can it help us reimagine what “AI success” looks like?

In late October 2024, NVIDIA’s Jensen Huang and Denmark’s King Frederik X symbolically plugged in the country’s new AI supercomputer, Gefion.

Societal impact vs. monetization
Public-private cooperation vs. venture capital
Powered by renewable energy

What DICE does in this posting will be available 24x7x365 in the future [Christian]

On 11/20/2024, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, business, career development, changing business models, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, Daniel S. Christian, digital learning, distance education, education technology, elearning, emerging technologies, entrepreneurship, experimentation, faculty, future, future of higher education, game-changing environment, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, internet, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, library / librarians, lifelong learning, MBA, microlearning, multimedia, Natural Language Processing (NLP), neurodivergent/special needs, New "Amazon.com" of Higher Education, new business models, online learning, online media, online tutoring, personalized/customized learning, platforms, productivity / tips and tricks, remote teaching and learning, skills, staying relevant, student-related, surviving, teachers, teaching & learning, teaching online, technologies for your home, training / L&D, universities, vendors, videoconferencing, virtual field trips, virtual K-12 schools, Virtual Reality (VR) / worlds / learning, virtual tutoring, vision/possibilities, vocational / trades, voice recognition / voice enabled interfaces, web-based collaboration, Web3, webinars, workplace, by Daniel Christian

From DSC:
First of all, when you look at the following posting:

What Top Tech Skills Should You Learn for 2025? — from dice.com by Nick Kolakowski

…you will see that they outline which skills you should consider mastering in 2025 if you want to stay on top of the latest career opportunities. They then list more information about the skills, how you apply the skills, and WHERE to get those skills.

I assert that in the future, people will be able to see this information on a 24x7x365 basis.

Which jobs are in demand?
What skills do I need to do those jobs?
WHERE do I get/develop those skills?

And that last part (about the WHERE do I develop those skills) will pull from many different institutions, people, companies, etc.

BUT PEOPLE are the key! Oftentimes, we need to — and prefer to — learn with others!

Miscommunication Leads AI-Based Hiring Tools Astray — from adigaskell.org

Nearly every Fortune 500 company now uses artificial intelligence (AI) to screen resumes and assess test scores to find the best talent. However, new research from the University of Florida suggests these AI tools might not be delivering the results hiring managers expect.

The problem stems from a simple miscommunication between humans and machines: AI thinks it’s picking someone to hire, but hiring managers only want a list of candidates to interview.

Without knowing about this next step, the AI might choose safe candidates. But if it knows there will be another round of screening, it might suggest different and potentially stronger candidates.

AI agents explained: Why OpenAI, Google and Microsoft are building smarter AI agents — from digit.in by Jayesh Shinde

In the last two years, the world has seen a lot of breakneck advancement in the Generative AI space, right from text-to-text, text-to-image and text-to-video based Generative AI capabilities. And all of that’s been nothing short of stepping stones for the next big AI breakthrough – AI agents. According to Bloomberg, OpenAI is preparing to launch its first autonomous AI agent, which is codenamed ‘Operator,’ as soon as in January 2025.

Apparently, this OpenAI agent – or Operator, as it’s codenamed – is designed to perform complex tasks independently. By understanding user commands through voice or text, this AI agent will seemingly do tasks related to controlling different applications in the computer, send an email, book flights, and no doubt other cool things. Stuff that ChatGPT, Copilot, Google Gemini or any other LLM-based chatbot just can’t do on its own.

2025: The year ‘invisible’ AI agents will integrate into enterprise hierarchies — from venturebeat.com by Taryn Plumb

In the enterprise of the future, human workers are expected to work closely alongside sophisticated teams of AI agents.

According to McKinsey, generative AI and other technologies have the potential to automate 60 to 70% of employees’ work. And, already, an estimated one-third of American workers are using AI in the workplace — oftentimes unbeknownst to their employers.

However, experts predict that 2025 will be the year that these so-called “invisible” AI agents begin to come out of the shadows and take more of an active role in enterprise operations.

“Agents will likely fit into enterprise workflows much like specialized members of any given team,” said Naveen Rao, VP of AI at Databricks and founder and former CEO of MosaicAI.

State of AI Report 2024 Summary — from ai-supremacy.com by Michael Spencer
Part I, Consolidation, emergence and adoption.

Which AI Image Model Is the Best Speller? Let’s Find Out! — from whytryai.com by Daniel Nest
I test 7 image models to find those that can actually write.

The contestants
I picked 7 participants for today’s challenge:

DALL-E 3 by OpenAI (via Microsoft Designer)
FLUX1.1 [pro] by Black Forest Labs (via Glif)
Ideogram 2.0 by Ideogram (via Ideogram)
Imagen 3 by Google (via Image FX)
Midjourney 6.1 by Midjourney (via Midjourney)
Recraft V3 by Recraft (via Recraft)
Stable Diffusion 3.5 Large by Stability AI (via Hugging Face)

How to get started with AI agents (and do it right) — from venturebeat.com by Taryn Plumb

So how can enterprises choose when to adopt third-party models, open source tools or build custom, in-house fine-tuned models? Experts weigh in.

OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI — from bloomberg.com (behind firewall)
Three of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.

OpenAI and others seek new path to smarter AI as current methods hit limitations — from reuters.com by Krystal Hu and Anna Tong

Summary

AI companies face delays and challenges with training new large language models
Some researchers are focusing on more time for inference in new models
Shift could impact AI arms race for resources like chips and energy

NVIDIA Advances Robot Learning and Humanoid Development With New AI and Simulation Tools — from blogs.nvidia.com by Spencer Huang
New Project GR00T workflows and AI world model development technologies to accelerate robot dexterity, control, manipulation and mobility.

How Generative AI is Revolutionizing Product Development — from intelligenthq.com

A recent report from McKinsey predicts that generative AI could unlock up to $2.6 to $4.4 annually trillion in value within product development and innovation across various industries. This staggering figure highlights just how significantly generative AI is set to transform the landscape of product development. Generative AI app development is driving innovation by using the power of advanced algorithms to generate new ideas, optimize designs, and personalize products at scale. It is also becoming a cornerstone of competitive advantage in today’s fast-paced market. As businesses look to stay ahead, understanding and integrating technologies like generative AI app development into product development processes is becoming more crucial than ever.

What are AI Agents: How To Create a Based AI Agent — from ccn.com by Lorena Nessi

Key Takeaways

AI agents handle complex, autonomous tasks beyond simple commands, showcasing advanced decision-making and adaptability.
The Based AI Agent template by Coinbase and Replit provides an easy starting point for developers to build blockchain-enabled AI agents.
AI based agents specifically integrate with blockchain, supporting crypto wallets and transactions.
Securing API keys in development is crucial to protect the agent from unauthorized access.

What are AI Agents and How Are They Used in Different Industries? — from rtinsights.com by Salvatore Salamone
AI agents enable companies to make smarter, faster, and more informed decisions. From predictive maintenance to real-time process optimization, these agents are delivering tangible benefits across industries.

“How to File a Lawsuit by Yourself: A Simple Guide” [Slone] — DC: Will there be more of this in the future?

On 11/13/2024, in 21st century, 24x7x365 access, Access to Justice (A2J), experimentation, ideas, innovation, vendors, Virtual courts and law firms, vision/possibilities, web-based collaboration, by Daniel Christian

How to File a Lawsuit by Yourself: A Simple Guide — from courtroom5.com by Debra Slone

I can say from personal experience that when you know how to file a lawsuit on your own, you’re more likely to assert your rights in all walks of life. Simply understanding the process of taking someone to court can change your life.

Introduction
Filing a civil lawsuit without a lawyer can be challenging, but many people do it to stand up for their rights. At Courtroom5, we understand the courage it takes to represent yourself, and we’re here to help. This guide will give you the essential knowledge and steps to file a civil lawsuit on your own. With clear instructions and practical tools, we aim to make the process easier and boost your confidence as you start your case.

Self-representation, or “pro se” litigation, requires more than basic knowledge of the law. It involves research, preparation, and understanding court rules. Our goal is to break down these tasks, making each step manageable from filing to finishing your case.

From DSC:
I haven’t used this site myself. But I post this item because we have a MAJOR issue here in the U.S. with Access To Justice (A2J) — the vast majority of CIVIL lawsuits are heavily tilted towards those who know how the game is played. The winners know what to do, they’ve been trained. But those without representation lose most of the time.

So I’m hoping that such online-based materials and services — including AI-based tools and platforms — can significantly alter this troublesome situation. So that’s why I’m posting this.

Using AI to brainstorm students own learning objectives [Potkalitsky] + other items re: AI in our learning ecosystems

On 11/13/2024, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Canvas - and other Instructure-related items, change, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education, education technology, educational games / serious games, emerging technologies, ethics, experimentation, faculty, formal learning, future, future of higher education, game-changing environment, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, informal learning, 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, learning spaces, liberal arts, mathematics, morals/values, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, technologies for your home, tools, UK, United States, universities, vendors, youth, by Daniel Christian

“The Value of Doing Things: What AI Agents Mean for Teachers” — from nickpotkalitsky.substack.com by guest author Jason Gulya, Professor of English and Applied Media at Berkeley College in New York City

AI Agents make me nervous. Really nervous.

I wish they didn’t.

I wish I could write that the last two years have made me more confident, more self-assured that AI is here to augment workers rather than replace them.

But I can’t.

I wish I could write that I know where schools and colleges will end up. I wish I could say that AI Agents will help us get where we need to be.

But I can’t.

At this point, today, I’m at a loss. I’m not sure where the rise of AI agents will take us, in terms of how we work and learn. I’m in the question-asking part of my journey. I have few answers.

So, let’s talk about where (I think) AI Agents will take education. And who knows? Maybe as I write I’ll come up with something more concrete.

It’s worth a shot, right?

From DSC:
I completely agree with Jason’s following assertion:

A good portion of AI advancement will come down to employee replacement. And AI Agents push companies towards that.

THAT’s where/what the ROI will be for corporations. They will make their investments up in the headcount area, and likely in other areas as well (product design, marketing campaigns, engineering-related items, and more). But how much time it takes to get there is a big question mark.

One last quote here…it’s too good not to include:

Behind these questions lies a more abstract, more philosophical one: what is the relationship between thinking and doing in a world of AI Agents and other kinds of automation?

How Good are Claude, ChatGPT & Gemini at Instructional Design? — from drphilippahardman.substack.com by Dr Philippa Hardman
A test of AI’s Instruction Design skills in theory & in practice

By examining models across three AI families—Claude, ChatGPT, and Gemini—I’ve started to identify each model’s strengths, limitations, and typical pitfalls.

Spoiler: my findings underscore that until we have specialised, fine-tuned AI copilots for instructional design, we should be cautious about relying on general-purpose models and ensure expert oversight in all ID tasks.

From DSC — I’m going to (have Nick) say this again:
I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing.

Students began mapping out research directions I’d never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns.

The Digital Literacy Quest: Become an AI Hero — from gamma.app

From DSC:
I have not gone through all of these online-based materials, but I like what they are trying to get at:

Confidence with AI
Students gain practical skills and confidence in using AI tools effectively.
Ethical Navigation
Learn to navigate the ethical landscape of AI with integrity and responsibility. Make informed decisions about AI usage.
Mastering Essential Skills
Develop critical thinking and problem-solving skills in the context of AI.

Expanding access to the Gemini app for teen students in education — from workspaceupdates.googleblog.com

Google Workspace for Education admins can now turn on the Gemini app with added data protection as an additional service for their teen users (ages 13+ or the applicable age in your country) in the following languages and countries. With added data protection, chats are not reviewed by human reviewers or otherwise used to improve AI models. The Gemini app will be a core service in the coming weeks for Education Standard and Plus users, including teens,

5 Essential Questions Educators Have About AI — from edsurge.com by Annie Ning

Recently, I spoke with several teachers regarding their primary questions and reflections on using AI in teaching and learning. Their thought-provoking responses challenge us to consider not only what AI can do but what it means for meaningful and equitable learning environments. Keeping in mind these reflections, we can better understand how we move forward toward meaningful AI integration in education.

FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI — from epoch.ai
FrontierMath presents hundreds of unpublished, expert-level mathematics problems that specialists spend days solving. It offers an ongoing measure of AI complex mathematical reasoning progress.

We’re introducing FrontierMath, a benchmark of hundreds of original, expert-crafted mathematics problems designed to evaluate advanced reasoning capabilities in AI systems. These problems span major branches of modern mathematics—from computational number theory to abstract algebraic geometry—and typically require hours or days for expert mathematicians to solve.

Rising demand for AI courses in UK universities shows 453% growth as students adapt to an AI-driven job market — from edtechinnovationhub.com

The demand for artificial intelligence courses in UK universities has surged dramatically over the past five years, with enrollments increasing by 453%, according to a recent study by Currys, a UK tech retailer.

The study, which analyzed UK university admissions data and surveyed current students and recent graduates, reveals how the growing influence of AI is shaping students’ educational choices and career paths.

This growth reflects the broader trend of AI integration across industries, creating new opportunities while transforming traditional roles. With AI’s influence on career prospects rising, students and graduates are increasingly drawn to AI-related courses to stay competitive in a rapidly changing job market.

Learning Ecosystems

5 items re: AI in general

“How to File a Lawsuit by Yourself: A Simple Guide” [Slone] — DC: Will there be more of this in the future?

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