“Who to follow in AI” in 2024? — from ai-supremacy.com by Michael Spencer
Part III – #35-55 – I combed the internet, I found the best sources of AI insights, education and articles. LinkedIn | Newsletters | X | YouTube | Substack | Threads | Podcasts

This list features both some of the best Newsletters on AI and people who make LinkedIn posts about AI papers, advances and breakthroughs. In today’s article we’ll be meeting the first 19-34, in a list of 180+.

Newsletter Writers
YouTubers
Engineers
Researchers who write
Technologists who are Creators
AI Educators
AI Evangelists of various kinds
Futurism writers and authors

I have been sharing the list in reverse chronological order on LinkedIn here.


Inside Google’s 7-Year Mission to Give AI a Robot Body — from wired.com by Hans Peter Brondmo
As the head of Alphabet’s AI-powered robotics moonshot, I came to believe many things. For one, robots can’t come soon enough. For another, they shouldn’t look like us.


Learning to Reason with LLMs — from openai.com
We are introducing OpenAI o1, a new large language model trained with reinforcement learning to perform complex reasoning. o1 thinks before it answers—it can produce a long internal chain of thought before responding to the user.


Items re: Microsoft Copilot:

Also see this next video re: Copilot Pages:


Sal Khan on the critical human skills for an AI age — from time.com by Kevin J. Delaney

As a preview of the upcoming Summit interview, here are Khan’s views on two critical questions, edited for space and clarity:

  1. What are the enduring human work skills in a world with ever-advancing AI? Some people say students should study liberal arts. Others say deep domain expertise is the key to remaining professionally relevant. Others say you need to have the skills of a manager to be able to delegate to AI. What do you think are the skills or competencies that ensure continued relevance professionally, employability, etc.?
  2. A lot of organizations are thinking about skills-based approaches to their talent. It involves questions like, ‘Does someone know how to do this thing or not?’ And what are the ways in which they can learn it and have some accredited way to know they actually have done it? That is one of the ways in which people use Khan Academy. Do you have a view of skills-based approaches within workplaces, and any thoughts on how AI tutors and training fit within that context?

 

Georgia Tech Aims to Take Lifetime Learning from Pastime to Pro — from workshift.org by Lilah Burke

As Americans live and work longer, many now find themselves needing to change jobs and careers several times within their lifetimes.

Now, Georgia Institute of Technology has created a new college to serve just these learners. Georgia Tech last week launched its College of Lifetime Learning, which will combine degree programs with non-degree programs, and seeks to educate 114K students by 2030. That would enable the university to double the current number of degrees granted and nondegree students served.

“What we’re hearing is that with the advancing pace of digitization taking place, changing demographics, people working longer, for example, higher ed needs to do something in addition to what it already has been doing” says Nelson Baker, interim dean of the new college.


Also see:

Is the Workplace the New College Campus? — from workshift.org by Joe Edelheit Ross

Now a quarter way through the 21st century, higher education is again in need of a reboot. Post Covid, colleges are closing one per week. More than 40M U.S. learners have started college but never finished. Nearly two-thirds of those learners would complete their degree but can’t afford to. Student debt now sits at almost $2T. Americans are losing faith in higher education.

Enter the apprenticeship degree, where students can earn a debt-free, four-year degree entirely embedded within a full-time, paid job. In the U.K., with government tax incentives, the apprenticeship-to-degree model has surged in eight years from zero to 50K new enrollments, making progress toward an expected 20% of postsecondary starts within the decade. As I have previously written, I believe the apprenticeship degree is just what American higher education needs to meet the moment.

 

The Most Popular AI Tools for Instructional Design (September, 2024) — from drphilippahardman.substack.com by Dr. Philippa Hardman
The tools we use most, and how we use them

This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.

My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?

Here’s where we are in September, 2024:


Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby,  Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)

As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.



The Impact of AI in Advancing Accessibility for Learners with Disabilities — from er.educause.edu by Rob Gibson

AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.


 

Risepoint Releases Voice of the Online Learner Report — from academicpartnerships.com by Risepoint; via Jeff Selingo on LinkedIn

The Voice of the Online Learner report highlights the journey of online learners, and the vital role education plays in their personal and professional growth and development. This year’s report compiled responses from over 3,400 prospective, current, and recently graduated online learners.

Key findings from this year’s Voice of the Online Learner report include:

  • Decision Factors for Online Students: When evaluating online programs, the key decision for students is cost, with 86% saying it’s extremely or very important. After cost, 84% said accreditation is most important, 75% said program concentrations, followed by 68% of respondents who said it was the time it took to achieve a degree. 38% selected the lowest cost program they evaluated (up from 29% in 2023).
  • Perception of Online Programs: Students see online programs as equally valid or better at meeting their needs than on-campus degree programs. 83% of respondents prefer the flexibility of online programs over hybrid or on-campus options, while 90% feel online programs are comparable to or better than an on-campus degree. 83% (up from 71% last year) want no on campus requirement.
  • Degree ROI: 92% of students who graduated from online degree programs reported tangible benefits to their career, including 44% who received a salary increase.
  • Value of the Degree: Career outcomes continue to be very important for students pursuing their degree.86% felt their degrees were important in achieving their career goals, and 61% of online undergraduates are likely to enroll in additional online degree programs to stay competitive.
  • Importance of Local Programs: Attending a university or college in the state where the student lives and works is also an important decision factor, with 70% enrolled at a higher education institution in the state where they live and/or work. These students say that local proximity creates greater trust, and that they also want to ensure the programs meet local licensing or accreditation requirements, when relevant.
  • Demographics: The average age for online students enrolled in undergraduate programs is 36 years old, while the average age for students enrolled in graduate programs is 38 years old. Of the students enrolled in undergraduate programs, 40% are first-generation college students.
  • Upskilling is lifelong: 86% of graduated and currently enrolled students are likely to do another online program in the future to upskill.
  • Generative AI is a concern: Students want guidance on generative AI, but 75% reported they have received none. 40% of students think it will affect their career positively and 40% believe it will impact them negatively. Nearly half (48%) have used it to help them study.
 

The Six AI Use Case Families of Instructional Design — from drphilippahardman.substack.com by Dr. Phillipa Harman
Pushing AI beyond content creation

So what are the six families? Here’s the TLDR:

  1. Creative Ideation, aka using AI to spark novel ideas and innovative design concepts.
  2. Research & Analysis, aka using AI to rapidly gather and synthesise information from vast sources.
  3. Data-Driven Insights, aka using AI to extract meaningful patterns and predictions from complex datasets.
  4. …and more

Town Hall: Back to School with AI — from gettingsmart.com

Key Points

  • AI can help educators focus more on human interaction and critical thinking by automating tasks that consume time but don’t require human empathy or creativity.
  • Encouraging students to use AI as a tool for learning and creativity can significantly boost their engagement and self-confidence, as seen in examples from student experiences shared in the discussion.

The speakers discuss various aspects of AI, including its potential to augment human intelligence and the need to focus on uniquely human competencies in the face of technological advancements. They also emphasize the significance of student agency, with examples of student-led initiatives and feedback sessions that reveal how young learners are already engaging with AI in innovative ways. The episode underscores the necessity for educators and administrators to stay informed and actively participate in the ongoing dialogue about AI to ensure its effective and equitable implementation in schools.


The video below is from The Artifice of Twinning by Marc Watkins


How AI Knocks Down Classroom Barriers — from gettingsmart.com by Alyssa Faubion

Key Points

  • AI can be a powerful tool to break down language, interest, and accessibility barriers in the classroom, making learning more inclusive and engaging.
  • Incorporating AI tools in educational settings can help build essential skills that AI can’t replace, such as creativity and problem-solving, preparing students for future job markets.

 

What Students Want: Key Results from DEC Global AI Student Survey 2024 — from digitaleducationcouncil.com by Digital Education Council

  • 86% of students globally are regularly using AI in their studies, with 54% of them using AI on a weekly basis, the recent Digital Education Council Global AI Student Survey found.
  • ChatGPT was found to be the most widely used AI tool, with 66% of students using it, and over 2 in 3 students reported using AI for information searching.
  • Despite their high rates of AI usage, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.

Chatting with WEF about ChatGPT in the classroom — from futureofbeinghuman.com by Andrew Maynard
A short video on generative AI in education from the World Economic Forum


The Post-AI Instructional Designer — from drphilippahardman.substack.com by Dr. Philippa Hardman
How the ID role is changing, and what this means for your key skills, roles & responsibilities

Specifically, the study revealed that teachers who reported most productivity gains were those who used AI not just for creating outputs (like quizzes or worksheets) but also for seeking input on their ideas, decisions and strategies.

Those who engaged with AI as a thought partner throughout their workflow, using it to generate ideas, define problems, refine approaches, develop strategies and gain confidence in their decisions gained significantly more from their collaboration with AI than those who only delegated functional tasks to AI.  


Leveraging Generative AI for Inclusive Excellence in Higher Education — from er.educause.edu by Lorna Gonzalez, Kristi O’Neil-Gonzalez, Megan Eberhardt-Alstot, Michael McGarry and Georgia Van Tyne
Drawing from three lenses of inclusion, this article considers how to leverage generative AI as part of a constellation of mission-centered inclusive practices in higher education.

The hype and hesitation about generative artificial intelligence (AI) diffusion have led some colleges and universities to take a wait-and-see approach.Footnote1 However, AI integration does not need to be an either/or proposition where its use is either embraced or restricted or its adoption aimed at replacing or outright rejecting existing institutional functions and practices. Educators, educational leaders, and others considering academic applications for emerging technologies should consider ways in which generative AI can complement or augment mission-focused practices, such as those aimed at accessibility, diversity, equity, and inclusion. Drawing from three lenses of inclusion—accessibility, identity, and epistemology—this article offers practical suggestions and considerations that educators can deploy now. It also presents an imperative for higher education leaders to partner toward an infrastructure that enables inclusive practices in light of AI diffusion.

An example way to leverage AI:

How to Leverage AI for Identity Inclusion
Educators can use the following strategies to intentionally design instructional content with identity inclusion in mind.

  • Provide a GPT or AI assistant with upcoming lesson content (e.g., lecture materials or assignment instructions) and ask it to provide feedback (e.g., troublesome vocabulary, difficult concepts, or complementary activities) from certain perspectives. Begin with a single perspective (e.g., first-time, first-year student), but layer in more to build complexity as you interact with the GPT output.

Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly
As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.

To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.

Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development. Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.


7 Ways to Use AI Music in Your Classroom — from classtechtips.com by Monica Burns


Change blindness — from oneusefulthing.org by Ethan Mollick
21 months later

I don’t think anyone is completely certain about where AI is going, but we do know that things have changed very quickly, as the examples in this post have hopefully demonstrated. If this rate of change continues, the world will look very different in another 21 months. The only way to know is to live through it.


My AI Breakthrough — from mgblog.org by Miguel Guhlin

Over the subsequent weeks, I’ve made other adjustments, but that first one was the one I asked myself:

  1. What are you doing?
  2. Why are you doing it that way?
  3. How could you change that workflow with AI?
  4. Applying the AI to the workflow, then asking, “Is this what I was aiming for? How can I improve the prompt to get closer?”
  5. Documenting what worked (or didn’t). Re-doing the work with AI to see what happened, and asking again, “Did this work?”

So, something that took me WEEKS of hard work, and in some cases I found impossible, was made easy. Like, instead of weeks, it takes 10 minutes. The hard part? Building the prompt to do what I want, fine-tuning it to get the result. But that doesn’t take as long now.

 

Augmented Course Design: Using AI to Boost Efficiency and Expand Capacity — from er.educause.edu by Berlin Fang and Kim Broussard
The emerging class of generative AI tools has the potential to significantly alter the landscape of course development.

Using generative artificial intelligence (GenAI) tools such as ChatGPT, Gemini, or CoPilot as intelligent assistants in instructional design can significantly enhance the scalability of course development. GenAI can significantly improve the efficiency with which institutions develop content that is closely aligned with the curriculum and course objectives. As a result, institutions can more effectively meet the rising demand for flexible and high-quality education, preparing a new generation of future professionals equipped with the knowledge and skills to excel in their chosen fields.1 In this article, we illustrate the uses of AI in instructional design in terms of content creation, media development, and faculty support. We also provide some suggestions on the effective and ethical uses of AI in course design and development. Our perspectives are rooted in medical education, but the principles can be applied to any learning context.

Table 1 summarizes a few low-hanging fruits in AI usage in course development.
.

Table 1. Types of Use of GenAI in Course Development
Practical Use of AI Use Scenarios and Examples
Inspiration
  • Exploring ideas for instructional strategies
  • Exploring ideas for assessment
  • Course mapping
  • Lesson or unit content planning
Supplementation
  • Text to audio
  • Transcription for audio
  • Alt text auto-generation
  • Design optimization (e.g., using Microsoft PPT Design)
Improvement
  • Improving learning objectives
  • Improving instructional materials
  • Improving course content writing (grammar, spelling, etc.)
Generation
  • Creating a PowerPoint draft using learning objectives
  • Creating peripheral content materials (introductions, conclusions)
  • Creating decorative images for content
Expansion
  • Creating a scenario based on learning objectives
  • Creating a draft of a case study
  • Creating a draft of a rubric

.


Also see:

10 Ways Artificial Intelligence Is Transforming Instructional Design — from er.educause.edu by Rob Gibson
Artificial intelligence (AI) is providing instructors and course designers with an incredible array of new tools and techniques to improve the course design and development process. However, the intersection of AI and content creation is not new.

I have been telling my graduate instructional design students that AI technology is not likely to replace them any time soon because learning and instruction are still highly personalized and humanistic experiences. However, as these students embark on their careers, they will need to understand how to appropriately identify, select, and utilize AI when developing course content. Examples abound of how instructional designers are experimenting with AI to generate and align student learning outcomes with highly individualized course activities and assessments. Instructional designers are also using AI technology to create and continuously adapt the custom code and power scripts embedded into the learning management system to execute specific learning activities.Footnote1 Other useful examples include scripting and editing videos and podcasts.

Here are a few interesting examples of how AI is shaping and influencing instructional design. Some of the tools and resources can be used to satisfy a variety of course design activities, while others are very specific.


Taking the Lead: Why Instructional Designers Should Be at the Forefront of Learning in the Age of AI — from medium.com by Rob Gibson
Education is at a critical juncture and needs to draw leaders from a broader pool, including instructional designers

The world of a medieval stone cutter and a modern instructional designer (ID) may seem separated by a great distance, but I wager any ID who upon hearing the story I just shared would experience an uneasy sense of déjà vu. Take away the outward details, and the ID would recognize many elements of the situation: the days spent in projects that fail to realize the full potential of their craft, the painful awareness that greater things can be built, but are unlikely to occur due to a poverty of imagination and lack of vision among those empowered to make decisions.

Finally, there is the issue of resources. No stone cutter could ever hope to undertake a large-scale enterprise without a multitude of skilled collaborators and abundant materials. Similarly, instructional designers are often departments of one, working in scarcity environments, with limited ability to acquire resources for ambitious projects and — just as importantly — lacking the authority or political capital needed to launch significant initiatives. For these reasons, instructional design has long been a profession caught in an uncomfortable stasis, unable to grow, evolve and achieve its full potential.

That is until generative AI appeared on the scene. While the discourse around AI in education has been almost entirely about its impact on teaching and assessment, there has been a dearth of critical analysis regarding AI’s potential for impacting instructional design.

We are at a critical juncture for AI-augmented learning. We can either stagnate, missing opportunities to support learners while educators continue to debate whether the use of generative AI tools is a good thing, or we can move forward, building a transformative model for learning akin to the industrial revolution’s impact.

Too many professional educators remain bound by traditional methods. The past two years suggest that leaders of this new learning paradigm will not emerge from conventional educational circles. This vacuum of leadership can be filled, in part, by instructional designers, who are prepared by training and experience to begin building in this new learning space.

 

Building a Collaborative Lifelong Learning Ecosystem — from by Bryan Benjamin and Amrit Ahluwalia

Staying current and relevant is essential for institutions in today’s rapidly evolving higher education landscape. However, innovative work cannot be accomplished in isolation.

On this episode, Bryan Benjamin, Executive Director of The Ivey Academy and Amrit Ahluwalia, Executive Director of Continuing Studies at Western University, discusses the importance of institutional collaboration and creating a scalable lifelong learning ecosystem.

 

Colleges Race to Ready Students for the AI Workplace — from wsj.com by Milla Surjadi (behind a paywall)
Non-techie students are learning basic generative-AI skills as schools revamp their course offerings to be more job-friendly

College students are desperate to add a new skill to their résumés: artificial intelligence.

The rise of generative AI in the workplace and students’ demands for more hirable talents are driving schools to revamp courses and add specialized degrees at speeds rarely seen in higher education. Schools are even going so far as to emphasize that all undergraduates get a taste of the tech, teaching them how to use AI in a given field—as well as its failings and unethical applications.


Speaking of AI, also see Educause’s Artificial Intelligence (AI)-related resources, which includes the following excerpt:

The Basics of AI in Higher Education

 

As the economy slows, focus on the skills of the future: Ability to change. — from joshbersin.com by Josh Bersin

The Skills Of The Future Are Clear: Ability To Drive Change
I had an interesting set of meetings today with a group of HR leaders we talk with every few weeks. Every single one of the CHROs and other leaders told us they are investing in “change management” and “business transformation” skills in their people. What does that mean?

It means just this. While we all want more engineers, manufacturing gurus, scientists, and sales and marketing experts in our companies, the biggest set of “skills” we need is the “ability to drive change.” That particular skill is quite complex, learned over time, and massively important at the moment. And that led me to my final point.

 

For college students—and for higher ed itself—AI is a required course — from forbes.com by Jamie Merisotis

Some of the nation’s biggest tech companies have announced efforts to reskill people to avoid job losses caused by artificial intelligence, even as they work to perfect the technology that could eliminate millions of those jobs.

It’s fair to ask, however: What should college students and prospective students, weighing their choices and possible time and financial expenses, think of this?

The news this spring was encouraging for people seeking to reinvent their careers to grab middle-class jobs and a shot at economic security.

 


Addressing Special Education Needs With Custom AI Solutions — from teachthought.com
AI can offer many opportunities to create more inclusive and effective learning experiences for students with diverse learning profiles.

For too long, students with learning disabilities have struggled to navigate a traditional education system that often fails to meet their unique needs. But what if technology could help bridge the gap, offering personalized support and unlocking the full potential of every learner?

Artificial intelligence (AI) is emerging as a powerful ally in special education, offering many opportunities to create more inclusive and effective learning experiences for students with diverse learning profiles.

.


 

.


11 Summer AI Developments Important to Educators — from stefanbauschard.substack.com by Stefan Bauschard
Equity demands that we help students prepare to thrive in an AI-World

*SearchGPT
*Smaller & on-device (phones, glasses) AI models
*AI TAs
*Access barriers decline, equity barriers grow
*Claude Artifacts and Projects
*Agents, and Agent Teams of a million+
*Humanoid robots & self-driving cars
*AI Curricular integration
*Huge video and video-segmentation gains
*Writing Detectors — The final blow
*AI Unemployment, Student AI anxiety, and forward-thinking approaches
*Alternative assessments


Academic Fracking: When Publishers Sell Scholars Work to AI — from aiedusimplified.substack.com by Lance Eaton
Further discussion of publisher practices selling scholars’ work to AI companies

Last week, I explored AI and academic publishing in response to an article that came out a few weeks ago about a deal Taylor & Francis made to sell their books to Microsoft and one other AI company (unnamed) for a boatload of money.

Since then, two more pieces have been widely shared including this piece from Inside Higher Ed by Kathryn Palmer (and to which I was interviewed and mentioned in) and this piece from Chronicle of Higher Ed by Christa Dutton. Both pieces try to cover the different sides talking to authors, scanning the commentary online, finding some experts to consult and talking to the publishers. It’s one of those things that can feel like really important and also probably only to a very small amount of folks that find themselves thinking about academic publishing, scholarly communication, and generative AI.


At the Crossroads of Innovation: Embracing AI to Foster Deep Learning in the College Classroom — from er.educause.edu by Dan Sarofian-Butin
AI is here to stay. How can we, as educators, accept this change and use it to help our students learn?

The Way Forward
So now what?

In one respect, we already have a partial answer. Over the last thirty years, there has been a dramatic shift from a teaching-centered to a learning-centered education model. High-impact practices, such as service learning, undergraduate research, and living-learning communities, are common and embraced because they help students see the real-world connections of what they are learning and make learning personal.11

Therefore, I believe we must double down on a learning-centered model in the age of AI.

The first step is to fully and enthusiastically embrace AI.

The second step is to find the “jagged technological frontier” of using AI in the college classroom.


.

.


.

.


Futures Thinking in Education — from gettingsmart.com by Getting Smart Staff

Key Points

  • Educators should leverage these tools to prepare for rapid changes driven by technology, climate, and social dynamics.
  • Cultivating empathy for future generations can help educators design more impactful and forward-thinking educational practices.
 

Gig Work, College Skills — from the-job.beehiiv.com by Paul Fain
New partnership lets college students use classroom learning for freelance roles.

Bringing Freelancing to College Education
A new partnership between Podium Education, an experiential learning company, and the freelance platform Upwork aims to let more students use the skills they’ve learned in class—and to make money now for doing so.

The Big Idea: The partnership, announced today, is an extension of the work that Podium already does with more than 70 universities. Through their Global Career Accelerator, students learn marketing, data analytics, or coding skills for credit and get the chance to work on a specific project with companies like Intel and the nonprofit charity: water. With the new partnership, students who complete the coursework will get customized access to and onboarding with Upwork, as well as coaching on how to be successful in freelancing.

 

Building Durable Skills into Middle School Career Exploration — from edmentum.com

As the needs of the modern workforce evolve at an unprecedented rate, durable, or “soft,” skills are often eclipsing demand for sought-after technical skills in high-demand jobs across industry sectors, geography, and educational level.

Through research, collaboration, and feedback from more than 800 educators, workforce professionals, industry leaders, and policymakers, America Succeeds—a leading educational policy and advocacy group—has developed Durable Skills and the Durable Skills Advantage Framework to provide a common language for the most in-demand durable skills. With 85% of career success being dependent on durable skills, this framework bridges the gap between the skills students are taught in school and evolving workforce needs.


On a somewhat related note, also see:

Green Workforce Connect and Building Green Pathways with Cynthia Finley — from gettingsmart.com by Mason Pashia

Over the last few years, we’ve been covering New Pathways, which we think of as a framework for school leaders and community members to create supports and systems that set students up for success in what’s next. This might be career exploration, client-connected projects, internships, or entrepreneurial experiences.

But what it really comes down to is connecting learners to real-world experiences and people and helping them articulate the skills that they gain in the process. Along the way, we began to talk a lot about green jobs. Many of the pre-existing pathways in secondary schools point towards CTE programs and trades, which are more in demand than they’ve been in decades.

This coincides with a pivotal moment in the arc of infrastructure redesign and development, one that heavily emphasizes clean energy trajectories and transferable skills. Many of these jobs we refer to as green pathways or requiring some of these green skills.

One leading organization in this space is the Interstate Renewable Energy Council or IREC. I got to sit down with Cynthia Finley, the Vice President of Workforce Strategy at IREC to talk about green pathways and what IREC is doing to increase awareness and exposure of green jobs and skills.

 

Per the Rundown AI:

Why it matters: AI is slowly shifting from a tool we text/prompt with, to an intelligence that we collaborate, learn, and grow with. Advanced Voice Mode’s ability to understand and respond to emotions in real-time convos could also have huge use cases in everything from customer service to mental health support.

Also relevant/see:


Creators to Have Personalized AI Assistants, Meta CEO Mark Zuckerberg Tells NVIDIA CEO Jensen Huang — from blogs.nvidia.com by Brian Caulfield
Zuckerberg and Huang explore the transformative potential of open source AI, the launch of AI Studio, and exchange leather jackets at SIGGRAPH 2024.

“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.

“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.

More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.

Also related/see:


From DSC:
Today was a MUCH better day for Nvidia however (up 12.81%). But it’s been very volatile in the last several weeks — as people and institutions ask where the ROI’s are going to come from.






9 compelling reasons to learn how to use AI Chatbots — from interestingengineering.com by Atharva Gosavi
AI Chatbots are conversational agents that can act on your behalf and converse with humans – a futuristic novelty that is already getting people excited about its usage in improving efficiency.

7. Accessibility and inclusivity
Chatbots can be designed to support multiple languages and accessibility needs, making services more inclusive. They can cater to users with disabilities by providing voice interaction capabilities and simplifying access to information. Understanding how to develop inclusive chatbots can help you contribute to making technology more accessible to everyone, a crucial aspect in today’s diverse society.

8. Future-proofing your skills
AI and automation are the future of work. Having the skills of building AI chatbots is a great way to future-proof your skills, and given the rising trajectory of AI, it’ll be a demanding skill in the market in the years to come. Staying ahead of technological trends is a great way to ensure you remain relevant and competitive in the job market.


Top 7 generative AI use cases for business — from cio.com by Grant Gross
Advanced chatbots, digital assistants, and coding helpers seem to be some of the sweet spots for gen AI use so far in business.

Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.

However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.

 

School 3.0: Reimagining Education in 2026, 2029, and 2034 — from davidborish.com by David Borish
.

The landscape of education is on the brink of a profound transformation, driven by rapid advancements in artificial intelligence. This shift was highlighted recently by Andrej Karpathy’s announcement of Eureka Labs, a venture aimed at creating an “AI-native” school. As we look ahead, it’s clear that the integration of AI in education will reshape how we learn, teach, and think about schooling altogether.

Traditional textbooks will begin to be replaced by interactive, AI-powered learning materials that adapt in real-time to a student’s progress.

As we approach 2029, the line between physical and virtual learning environments will blur significantly.

Curriculum design will become more flexible and personalized, with AI systems suggesting learning pathways based on each student’s interests, strengths, and career aspirations.

The boundaries between formal education and professional development will blur, creating a continuous learning ecosystem.

 
© 2024 | Daniel Christian