Open AI

“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, Australia, 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/staff, 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, the downsides of how people use tech, 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 The Learning Network; 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.”

15 Times to use AI, and 5 Not to — from oneusefulthing.org by Ethan Mollick
Notes on the Practical Wisdom of AI Use

There are several types of work where AI can be particularly useful, given the current capabilities and limitations of LLMs. Though this list is based in science, it draws even more from experience. Like any form of wisdom, using AI well requires holding opposing ideas in mind: it can be transformative yet must be approached with skepticism, powerful yet prone to subtle failures, essential for some tasks yet actively harmful for others. I also want to caveat that you shouldn’t take this list too seriously except as inspiration – you know your own situation best, and local knowledge matters more than any general principles. With all that out of the way, below are several types of tasks where AI can be especially useful, given current capabilities—and some scenarios where you should remain wary.

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.

AI Predators: What Schools Should Know and Do — from techlearning.com by Erik Ofgang
AI is increasingly be used by predators to connect with underage students online. Yasmin London, global online safety expert at Qoria and a former member of the New South Wales Police Force in Australia, shares steps educators can take to protect students.

The threat from AI for students goes well beyond cheating, says Yasmin London, global online safety expert at Qoria and a former member of the New South Wales Police Force in Australia.

Increasingly at U.S. schools and beyond, AI is being used by predators to manipulate children. Students are also using AI generate inappropriate images of other classmates or staff members. For a recent report, Qoria, a company that specializes in child digital safety and wellbeing products, surveyed 600 schools across North America, UK, Australia, and New Zealand.

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.

Increasing AI Fluency Among Enterprise Employees, Senior Management & Executives — from learningguild.com by Bill Brandon

This article attempts, in these early days, to provide some specific guidelines for AI curriculum planning in enterprise organizations.

The two reports identified in the first paragraph help to answer an important question. What can enterprise L&D teams do to improve AI fluency in their organizations?

You could be surprised how many software products have added AI features. Examples (to name a few) are productivity software (Microsoft 365 and Google Workspace); customer relationship management (Salesforce and Hubspot); human resources (Workday and Talentsoft); marketing and advertising (Adobe Marketing Cloud and Hootsuite); and communication and collaboration (Slack and Zoom). Look for more under those categories in software review sites.

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.

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.

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

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.

Is Generative AI and ChatGPT healthy for Students? — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky
Beyond Text Generation: How AI Ignites Student Discovery and Deep Thinking, according to firsthand experiences of Teachers and AI researchers like Nick Potkalitsky.

After two years of intensive experimentation with AI in education, I am witnessing something amazing unfolding before my eyes. While much of the world fixates on AI’s generative capabilities—its ability to create essays, stories, and code—my students have discovered something far more powerful: exploratory AI, a dynamic partner in investigation and critique that’s transforming how they think.
…
They’ve moved beyond the initial fascination with AI-generated content to something far more sophisticated: using AI as an exploratory tool for investigation, interrogation, and intellectual discovery.
…
Instead of the much-feared “shutdown” of critical thinking, we’re witnessing something extraordinary: the emergence of what I call “generative thinking”—a dynamic process where students learn to expand, reshape, and evolve their ideas through meaningful exploration with AI tools. Here I consciously reposition the term “generative” as a process of human origination, although one ultimately spurred on by machine input.

A Road Map for Leveraging AI at a Smaller Institution — from er.educause.edu by Dave Weil and Jill Forrester
Smaller institutions and others may not have the staffing and resources needed to explore and take advantage of developments in artificial intelligence (AI) on their campuses. This article provides a roadmap to help institutions with more limited resources advance AI use on their campuses.

The following activities can help smaller institutions better understand AI and lay a solid foundation that will allow them to benefit from it.

Understand the impact…
Understand the different types of AI tools…
Focus on institutional data and knowledge repositories…

Smaller institutions do not need to fear being left behind in the wake of rapid advancements in AI technologies and tools. By thinking intentionally about how AI will impact the institution, becoming familiar with the different types of AI tools, and establishing a strong data and analytics infrastructure, institutions can establish the groundwork for AI success. The five fundamental activities of coordinating, learning, planning and governing, implementing, and reviewing and refining can help smaller institutions make progress on their journey to use AI tools to gain efficiencies and improve students’ experiences and outcomes while keeping true to their institutional missions and values.

Also from Educause, see:

From Hype to Help: Making GenAI Useful for Enterprise Reporting and Data Analytics — from er.educause.edu by Craig Rudick

AI school opens – learners are not good or bad but fast and slow — from donaldclarkplanb.blogspot.com by Donald Clark

That is what they are doing here. Lesson plans focus on learners rather than the traditional teacher-centric model. Assessing prior strengths and weaknesses, personalising to focus more on weaknesses and less on things known or mastered. It’s adaptive, personalised learning. The idea that everyone should learn at the exactly same pace, within the same timescale is slightly ridiculous, ruled by the need for timetabling a one to many, classroom model.

For the first time in the history of our species we have technology that performs some of the tasks of teaching. We have reached a pivot point where this can be tried and tested. My feeling is that we’ll see a lot more of this, as parents and general teachers can delegate a lot of the exposition and teaching of the subject to the technology. We may just see a breakthrough that transforms education.

Agentic AI Named Top Tech Trend for 2025 — from campustechnology.com by David Ramel

Agentic AI will be the top tech trend for 2025, according to research firm Gartner. The term describes autonomous machine “agents” that move beyond query-and-response generative chatbots to do enterprise-related tasks without human guidance.
…
More realistic challenges that the firm has listed elsewhere include:

- Agentic AI proliferating without governance or tracking;
- Agentic AI making decisions that are not trustworthy;
- Agentic AI relying on low-quality data;
- Employee resistance; and
- Agentic-AI-driven cyberattacks enabling “smart malware.”

Also from campustechnology.com, see:

New OpenAI Swarm Framework Offers Experimental Tool for Multi-Agent AI Networks — by John K. Waters
OpenAI has introduced a new open source framework designed to simplify the development and management of multi-agent AI systems that can collaborate autonomously to perform tasks.

Three items from edcircuit.com:

All or nothing at Educause24 — from onedtech.philhillaa.com by Kevin Kelly
Looking for specific solutions at the conference exhibit hall, with an educator focus

Here are some notable trends:

Alignment with campus policies: …
Choose your own AI adventure: …
Integrate AI throughout a workflow: …
Moving from prompt engineering to bot building: …
More complex problem-solving: …

…
Not all AI news is good news. In particular, AI has exacerbated the problem of fraudulent enrollment–i.e., rogue actors who use fake or stolen identities with the intent of stealing financial aid funding with no intention of completing coursework.
…
The consequences are very real, including financial aid funding going to criminal enterprises, enrollment estimates getting dramatically skewed, and legitimate students being blocked from registering for classes that appear “full” due to large numbers of fraudulent enrollments.

? Introducing ChatGPT search ?

ChatGPT can now search the web in a much better way than before so you get fast, timely answers with links to relevant web sources.https://t.co/7yilNgqH9T pic.twitter.com/z8mJWS8J9c

— OpenAI (@OpenAI) October 31, 2024

ChatGPT Search just dropped, so of course, Google is dead. (Just kidding… probably ?)

But is it any good?

A ChatGPT Search vs. Perplexity vs. Google ?:

— Nathan Lands — Lore.com (@NathanLands) November 1, 2024

Google’s worst nightmare just became reality — from aidisruptor.ai by Alex McFarland
OpenAI just launched an all-out assault on traditional search engines.

Google’s worst nightmare just became reality. OpenAI didn’t just add search to ChatGPT – they’ve launched an all-out assault on traditional search engines.

It’s the beginning of the end for search as we know it.

Let’s be clear about what’s happening: OpenAI is fundamentally changing how we’ll interact with information online. While Google has spent 25 years optimizing for ad revenue and delivering pages of blue links, OpenAI is building what users actually need – instant, synthesized answers from current sources.

The rollout is calculated and aggressive: ChatGPT Plus and Team subscribers get immediate access, followed by Enterprise and Education users in weeks, and free users in the coming months. This staged approach is about systematically dismantling Google’s search dominance.

Big day for desktops.

Advanced Voice is now available in the macOS and Windows desktop apps.https://t.co/mv4ACwIhzA pic.twitter.com/HbwXbN9NkD

— OpenAI (@OpenAI) October 30, 2024

We’re starting to roll out the ability to search through your chat history on ChatGPT web.

Now you can quickly & easily bring up a chat to reference, or pick up a chat where you left off. pic.twitter.com/YVAOUpFvzJ

— OpenAI (@OpenAI) October 29, 2024

Open for AI: India Tech Leaders Build AI Factories for Economic Transformation — from blogs.nvidia.com
Yotta Data Services, Tata Communications, E2E Networks and Netweb are among the providers building and offering NVIDIA-accelerated infrastructure and software, with deployments expected to double by year’s end.

Some dangers of running AI’s that control a computer or a web browser; + other AI related items

On 10/30/2024, in Apple, Artificial Intelligence/Agents/LLMs/and Related, business, computer science, emerging technologies, Europe, Google, Microsoft, NVIDIA, Open AI, platforms, programming, the downsides of how people use tech, tools, trends, United States, vendors, workplace, by Daniel Christian

Claude can now write and run code.

We’ve added a new analysis tool. The tool helps Claude respond with mathematically precise and reproducible answers. You can then create interactive data visualizations with Artifacts.

Enable the feature preview: https://t.co/bJ8BjBT6zG. pic.twitter.com/Jq5xOHBmiR

— Anthropic (@AnthropicAI) October 24, 2024

Along these same lines, see:

Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku

We’re also introducing a groundbreaking new capability in public beta: computer use. Available today on the API, developers can direct Claude to use computers the way people do—by looking at a screen, moving a cursor, clicking buttons, and typing text. Claude 3.5 Sonnet is the first frontier AI model to offer computer use in public beta. At this stage, it is still experimental—at times cumbersome and error-prone. We’re releasing computer use early for feedback from developers, and expect the capability to improve rapidly over time.

ZombAIs: From Prompt Injection to C2 with Claude Computer Use — from embracethered.com by Johann Rehberger

A few days ago, Anthropic released Claude Computer Use, which is a model + code that allows Claude to control a computer. It takes screenshots to make decisions, can run bash commands and so forth.

It’s cool, but obviously very dangerous because of prompt injection. Claude Computer Use enables AI to run commands on machines autonomously, posing severe risks if exploited via prompt injection.

This blog post demonstrates that it’s possible to leverage prompt injection to achieve, old school, command and control (C2) when giving novel AI systems access to computers.
…
We discussed one way to get malware onto a Claude Computer Use host via prompt injection. There are countless others, like another way is to have Claude write the malware from scratch and compile it. Yes, it can write C code, compile and run it. There are many other options.

TrustNoAI.

And again, remember do not run unauthorized code on systems that you do not own or are authorized to operate on.

Also relevant here, see:

Perplexity Grows, GPT Traffic Surges, Gamma Dominates AI Presentations – The AI for Work Top 100: October 2024 — from flexos.work by Daan van Rossum
Perplexity continues to gain users despite recent controversies. Five out of six GPTs see traffic boosts. This month’s highest gainers including Gamma, Blackbox, Runway, and more.

Growing Up: Navigating Generative AI’s Early Years – AI Adoption Report — from ai.wharton.upenn.edu by Jeremy Korst, Stefano Puntoni, & Mary Purk

From a survey with more than 800 senior business leaders, this report’s findings indicate that weekly usage of Gen AI has nearly doubled from 37% in 2023 to 72% in 2024, with significant growth in previously slower-adopting departments like Marketing and HR. Despite this increased usage, businesses still face challenges in determining the full impact and ROI of Gen AI. Sentiment reports indicate leaders have shifted from feelings of “curiosity” and “amazement” to more positive sentiments like “pleased” and “excited,” and concerns about AI replacing jobs have softened. Participants were full-time employees working in large commercial organizations with 1,000 or more employees.

Apple study exposes deep cracks in LLMs’ “reasoning” capabilities — from arstechnica.com by Kyle Orland
Irrelevant red herrings lead to “catastrophic” failure of logical inference.

For a while now, companies like OpenAI and Google have been touting advanced “reasoning” capabilities as the next big step in their latest artificial intelligence models. Now, though, a new study from six Apple engineers shows that the mathematical “reasoning” displayed by advanced large language models can be extremely brittle and unreliable in the face of seemingly trivial changes to common benchmark problems.

The fragility highlighted in these new results helps support previous research suggesting that LLMs use of probabilistic pattern matching is missing the formal understanding of underlying concepts needed for truly reliable mathematical reasoning capabilities. “Current LLMs are not capable of genuine logical reasoning,” the researchers hypothesize based on these results. “Instead, they attempt to replicate the reasoning steps observed in their training data.”

Google CEO says more than a quarter of the company’s new code is created by AI — from businessinsider.in by Hugh Langley

More than a quarter of new code at Google is made by AI and then checked by employees.
Google is doubling down on AI internally to make its business more efficient.

Top Generative AI Chatbots by Market Share – October 2024

Bringing developer choice to Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview — from github.blog

We are bringing developer choice to GitHub Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview and o1-mini. These new models will be rolling out—first in Copilot Chat, with OpenAI o1-preview and o1-mini available now, Claude 3.5 Sonnet rolling out progressively over the next week, and Google’s Gemini 1.5 Pro in the coming weeks. From Copilot Workspace to multi-file editing to code review, security autofix, and the CLI, we will bring multi-model choice across many of GitHub Copilot’s surface areas and functions soon.

“AI-governed robots can easily be hacked” [Barsee], a new AI capability called “computer use” + numerous other items re: AI in general

On 10/23/2024, in Artificial Intelligence/Agents/LLMs/and Related, communications, communities of practice, computer science, content development, aggregation, repositories, corporate / business world, creativity, data related items, digital video, emerging technologies, Google, health, innovation, IT in HE, media/film, Microsoft, multimedia, new media literacies, Open AI, pace of change, platforms, presentations, productivity / tips and tricks, programming, research, robotics, society, the downsides of how people use tech, tools, United States, universities, vendors, writing, by Daniel Christian

AI-governed robots can easily be hacked — from theaivalley.com by Barsee
PLUS: Sam Altman’s new company “World” introduced…

In a groundbreaking study, researchers from Penn Engineering showed how AI-powered robots can be manipulated to ignore safety protocols, allowing them to perform harmful actions despite normally rejecting dangerous task requests.

What did they find ?

Researchers found previously unknown security vulnerabilities in AI-governed robots and are working to address these issues to ensure the safe use of large language models(LLMs) in robotics.
Their newly developed algorithm, RoboPAIR, reportedly achieved a 100% jailbreak rate by bypassing the safety protocols on three different AI robotic systems in a few days.
Using RoboPAIR, researchers were able to manipulate test robots into performing harmful actions, like bomb detonation and blocking emergency exits, simply by changing how they phrased their commands.

Why does it matter?

This research highlights the importance of spotting weaknesses in AI systems to improve their safety, allowing us to test and train them to prevent potential harm.

From DSC:
Great! Just what we wanted to hear. But does it surprise anyone? Even so…we move forward at warp speeds.

From DSC:
So, given the above item, does the next item make you a bit nervous as well? I saw someone on Twitter/X exclaim, “What could go wrong?” I can’t say I didn’t feel the same way.

Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku — from anthropic.com

We’re also introducing a groundbreaking new capability in public beta: computer use. Available today on the API, developers can direct Claude to use computers the way people do—by looking at a screen, moving a cursor, clicking buttons, and typing text. Claude 3.5 Sonnet is the first frontier AI model to offer computer use in public beta. At this stage, it is still experimental—at times cumbersome and error-prone. We’re releasing computer use early for feedback from developers, and expect the capability to improve rapidly over time.

Per The Rundown AI:

The Rundown: Anthropic just introduced a new capability called ‘computer use’, alongside upgraded versions of its AI models, which enables Claude to interact with computers by viewing screens, typing, moving cursors, and executing commands.
…
Why it matters: While many hoped for Opus 3.5, Anthropic’s Sonnet and Haiku upgrades pack a serious punch. Plus, with the new computer use embedded right into its foundation models, Anthropic just sent a warning shot to tons of automation startups—even if the capabilities aren’t earth-shattering… yet.

Also related/see:

What is Anthropic’s AI Computer Use? — from ai-supremacy.com by Michael Spencer
Task automation, AI at the intersection of coding and AI agents take on new frenzied importance heading into 2025 for the commercialization of Generative AI.
New Claude, Who Dis? — from theneurondaily.com
Anthropic just dropped two new Claude models…oh, and Claude can now use your computer.
When you give a Claude a mouse — from oneusefulthing.org by Ethan Mollick
Some quick impressions of an actual agent

Introducing Act-One — from runwayml.com
A new way to generate expressive character performances using simple video inputs.

Per Lore by Nathan Lands:

What makes Act-One special? It can capture the soul of an actor’s performance using nothing but a simple video recording. No fancy motion capture equipment, no complex face rigging, no army of animators required. Just point a camera at someone acting, and watch as their exact expressions, micro-movements, and emotional nuances get transferred to an AI-generated character.

Think about what this means for creators: you could shoot an entire movie with multiple characters using just one actor and a basic camera setup. The same performance can drive characters with completely different proportions and looks, while maintaining the authentic emotional delivery of the original performance. We’re witnessing the democratization of animation tools that used to require millions in budget and years of specialized training.

Also related/see:

Introducing, Act-One. A new way to generate expressive character performances inside Gen-3 Alpha using a single driving video and character image. No motion capture or rigging required.

Learn more about Act-One below.

(1/7) pic.twitter.com/p1Q8lR8K7G

— Runway (@runwayml) October 22, 2024

Google to buy nuclear power for AI datacentres in ‘world first’ deal — from theguardian.com
Tech company orders six or seven small nuclear reactors from California’s Kairos Power

Google has signed a “world first” deal to buy energy from a fleet of mini nuclear reactors to generate the power needed for the rise in use of artificial intelligence.

The US tech corporation has ordered six or seven small nuclear reactors (SMRs) from California’s Kairos Power, with the first due to be completed by 2030 and the remainder by 2035.

Related:

Three Mile Island nuclear plant will reopen to power Microsoft data centers — from npr.org

ChatGPT Topped 3 Billion Visits in September — from similarweb.com

After the extreme peak and summer slump of 2023, ChatGPT has been setting new traffic highs since May

ChatGPT has been topping its web traffic records for months now, with September 2024 traffic up 112% year-over-year (YoY) to 3.1 billion visits, according to Similarweb estimates. That’s a change from last year, when traffic to the site went through a boom-and-bust cycle.

Crazy “AI Army” — from aisecret.us

Also from aisecret.us, see World’s First Nuclear Power Deal For AI Data Centers

Google has made a historic agreement to buy energy from a group of small nuclear reactors (SMRs) from Kairos Power in California. This is the first nuclear power deal specifically for AI data centers in the world.

New updates to help creators build community, drive business, & express creativity on YouTube — from support.google.com

Hey creators!
Made on YouTube 2024 is here and we’ve announced a lot of updates that aim to give everyone the opportunity to build engaging communities, drive sustainable businesses, and express creativity on our platform.

Below is a roundup with key info – feel free to upvote the announcements that you’re most excited about and subscribe to this post to get updates on these features! We’re looking forward to another year of innovating with our global community it’s a future full of opportunities, and it’s all Made on YouTube!

New autonomous agents scale your team like never before — from blogs.microsoft.com

Today, we’re announcing new agentic capabilities that will accelerate these gains and bring AI-first business process to every organization.

First, the ability to create autonomous agents with Copilot Studio will be in public preview next month.
Second, we’re introducing ten new autonomous agents in Dynamics 365 to build capacity for every sales, service, finance and supply chain team.

10 Daily AI Use Cases for Business Leaders— from flexos.work by Daan van Rossum
While AI is becoming more powerful by the day, business leaders still wonder why and where to apply today. I take you through 10 critical use cases where AI should take over your work or partner with you.

Multi-Modal AI: Video Creation Simplified — from heatherbcooper.substack.com by Heather Cooper

Emerging Multi-Modal AI Video Creation Platforms
The rise of multi-modal AI platforms has revolutionized content creation, allowing users to research, write, and generate images in one app. Now, a new wave of platforms is extending these capabilities to video creation and editing.

Multi-modal video platforms combine various AI tools for tasks like writing, transcription, text-to-voice conversion, image-to-video generation, and lip-syncing. These platforms leverage open-source models like FLUX and LivePortrait, along with APIs from services such as ElevenLabs, Luma AI, and Gen-3.

AI Medical Imagery Model Offers Fast, Cost-Efficient Expert Analysis — from developer.nvidia.com/

Are ChatGPT, Claude & NotebookLM *Really* Disrupting Education? — from drphilippahardman.substack.com
Evaluating Gen AI’s *real* impact on human learning

The TLDR here is that, as useful as popular AI tools are for learners, as things stand they only enable us to take the very first steps on what is a long and complex journey of learning.

AI tools like ChatGPT 4o, Claude 3.5 & NotebookLM can help to give us access to information but (for now at least) the real work of learning remains in our – the humans’ – hands.

To which Anna Mills had a solid comment:

It might make a lot of sense to regulate generated audio to require some kind of watermark and/or metadata. Instructors who teach online and assign voice recordings, we need to recognize that these are now very easy and free to auto-generate. In some cases we are assigning this to discourage students from using AI to just autogenerate text responses, but audio is not immune.

10 ChatGPT prompts to extract everything from a book: pic.twitter.com/zzn4NrWu4l

— Farhan (@mhdfaran) October 12, 2024

Articulate AI & the “Buttonification” of Instructional Design — from drphilippahardman.substack.com by Dr. Philippa Hardman
A new trend in AI-UX, and its implications for Instructional Design

1. Using AI to Scale Exceptional Instructional Design Practice
Imagine a bonification system that doesn’t just automate tasks, but scales best practices in instructional design:

Evidence-Based Design Button…
Learner-Centered Objectives Generator…
Engagement Optimiser…

2. Surfacing AI’s Instructional Design Thinking
Instead of hiding AI’s decision-making process, what if we built an AI system which invites instructional designers to probe, question, and learn from an expert trained AI?

Explain This Design…
Show Me Alternatives…
Challenge My Assumptions…
Learning Science Insights…

By reimagining the role of AI in this way, we would…

Recapping OpenAI’s Education Forum — from marcwatkins.substack.com by Marc Watkins

OpenAI’s Education Forum was eye-opening for a number of reasons, but the one that stood out the most was Leah Belsky acknowledging what many of us in education had known for nearly two years—the majority of the active weekly users of ChatGPT are students. OpenAI has internal analytics that track upticks in usage during the fall and then drops off in the spring. Later that evening, OpenAI’s new CFO, Sarah Friar, further drove the point home with an anecdote about usage in the Philippines jumping nearly 90% at the start of the school year.

I had hoped to gain greater insight into OpenAI’s business model and how it related to education, but the Forum left me with more questions than answers. What app has the majority of users active 8 to 9 months out of the year and dormant for the holidays and summer breaks? What business model gives away free access and only converts 1 out of every 20-25 users to paid users? These were the initial thoughts that I hoped the Forum would address. But those questions, along with some deeper and arguably more critical ones, were skimmed over to drive home the main message of the Forum—Universities have to rapidly adopt AI and become AI-enabled institutions.

Off-Loading in the Age of Generative AI — from insidehighered.com by James DeVaney

As we embrace these technologies, we must also consider the experiences we need to discover and maintain our connections—and our humanity. In a world increasingly shaped by AI, I find myself asking: What are the experiences that define us, and how do they influence the relationships we build, both professionally and personally?

This concept of “off-loading” has become central to my thinking. In simple terms, off-loading is the act of delegating tasks to AI that we would otherwise do ourselves. As AI systems advance, we’re increasingly confronted with a question: Which tasks should we off-load to AI?

From DSC:
Great…we have another tool called Canvas. Or did you say Canva?

Introducing canvas — from OpenAI
A new way of working with ChatGPT to write and code

We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Canvas opens in a separate window, allowing you and ChatGPT to collaborate on a project. This early beta introduces a new way of working together—not just through conversation, but by creating and refining ideas side by side.

Canvas was built with GPT-4o and can be manually selected in the model picker while in beta. Starting today we’re rolling out canvas to ChatGPT Plus and Team users globally. Enterprise and Edu users will get access next week. We also plan to make canvas available to all ChatGPT Free users when it’s out of beta.

Using AI to buy your home? These companies think it’s time you should — from usatoday.com by Andrea Riquier

The way Americans buy homes is changing dramatically.

New industry rules about how home buyers’ real estate agents get paid are prompting a reckoning among housing experts and the tech sector. Many house hunters who are already stretched thin by record-high home prices and closing costs must now decide whether, and how much, to pay an agent.

A 2-3% commission on the median home price of $416,700 could be well over $10,000, and in a world where consumers are accustomed to using technology for everything from taxes to tickets, many entrepreneurs see an opportunity to automate away the middleman, even as some consumer advocates say not so fast.

The State of AI Report 2024 — from nathanbenaich.substack.com by Nathan Benaich

The Great Mismatch — from the-job.beehiiv.com. by Paul Fain
Artificial intelligence could threaten millions of decent-paying jobs held by women without degrees.

Women in administrative and office roles may face the biggest AI automation risk, find Brookings researchers armed with data from OpenAI. Also, why Indiana could make the Swiss apprenticeship model work in this country, and how learners get disillusioned when a certificate doesn’t immediately lead to a good job.
…
A major new analysis from the Brookings Institution, using OpenAI data, found that the most vulnerable workers don’t look like the rail and dockworkers who have recaptured the national spotlight. Nor are they the creatives—like Hollywood’s writers and actors—that many wealthier knowledge workers identify with. Rather, they’re predominantly women in the 19M office support and administrative jobs that make up the first rung of the middle class.

“Unfortunately the technology and automation risks facing women have been overlooked for a long time,” says Molly Kinder, a fellow at Brookings Metro and lead author of the new report. “Most of the popular and political attention to issues of automation and work centers on men in blue-collar roles. There is far less awareness about the (greater) risks to women in lower-middle-class roles.”

introducing swarm: an experimental framework for building, orchestrating, and deploying multi-agent systems. ?https://t.co/97n4fehmtM

— shyamal (@shyamalanadkat) October 11, 2024

Is this how AI will transform the world over the next decade? — from futureofbeinghuman.com by Andrew Maynard
Anthropic’s CEO Dario Amodei has just published a radical vision of an AI-accelerated future. It’s audacious, compelling, and a must-read for anyone working at the intersection of AI and society.

But if Amodei’s essay is approached as a conversation starter rather than a manifesto — which I think it should be — it’s hard to see how it won’t lead to clearer thinking around how we successfully navigate the coming AI transition.

Given the scope of the paper, it’s hard to write a response to it that isn’t as long or longer as the original. Because of this, I’d strongly encourage anyone who’s looking at how AI might transform society to read the original — it’s well written, and easier to navigate than its length might suggest.

That said, I did want to pull out a few things that struck me as particularly relevant and important — especially within the context of navigating advanced technology transitions.

And speaking of that essay, here’s a summary from The Rundown AI:

Anthropic CEO Dario Amodei just published a lengthy essay outlining an optimistic vision for how AI could transform society within 5-10 years of achieving human-level capabilities, touching on longevity, politics, work, the economy, and more.

The details:

Amodei believes that by 2026, ‘powerful AI’ smarter than a Nobel Prize winner across fields, with agentic and all multimodal capabilities, will be possible.
He also predicted that AI could compress 100 years of scientific progress into 10 years, curing most diseases and doubling the human lifespan.
The essay argued AI could strengthen democracy by countering misinformation and providing tools to undermine authoritarian regimes.
The CEO acknowledged potential downsides, including job displacement — but believes new economic models will emerge to address this.
He envisions AI driving unprecedented economic growth but emphasizes ensuring AI’s benefits are broadly distributed.

Why it matters:

As the CEO of what is seen as the ‘safety-focused’ AI lab, Amodei paints a utopia-level optimistic view of where AI will head over the next decade. This thought-provoking essay serves as both a roadmap for AI’s potential and a call to action to ensure the responsible development of technology.

AI in the Workplace: Answering 3 Big Questions — from gallup.com by Kate Den Houter

However, most workers remain unaware of these efforts. Only a third (33%) of all U.S. employees say their organization has begun integrating AI into their business practices, with the highest percentage in white-collar industries (44%).
…
White-collar workers are more likely to be using AI. White-collar workers are, by far, the most frequent users of AI in their roles. While 81% of employees in production/frontline industries say they never use AI, only 54% of white-collar workers say they never do and 15% report using AI weekly.
…
Most employees using AI use it for idea generation and task automation. Among employees who say they use AI, the most common uses are to generate ideas (41%), to consolidate information or data (39%), and to automate basic tasks (39%).

Nvidia Blackwell GPUs sold out for the next 12 months as AI market boom continues — from techspot.com by Skye Jacobs
Analysts expect Team Green to increase its already formidable market share

Selling like hotcakes: The extraordinary demand for Blackwell GPUs illustrates the need for robust, energy-efficient processors as companies race to implement more sophisticated AI models and applications. The coming months will be critical to Nvidia as the company works to ramp up production and meet the overwhelming requests for its latest product.

Here’s my AI toolkit — from wondertools.substack.com by Jeremy Caplan and Nikita Roy
How and why I use the AI tools I do — an audio conversation

1. What are two useful new ways to use AI?

AI-powered research: Type a detailed search query into Perplexity instead of Google to get a quick, actionable summary response with links to relevant information sources. Read more of my take on why Perplexity is so useful and how to use it.
Notes organization and analysis: Tools like NotebookLM, Claude Projects, and Mem can help you make sense of huge repositories of notes and documents. Query or summarize your own notes and surface novel connections between your ideas.

How far should we go in allowing technology to aid our decision-making processes? [Schlegel] + other legaltech-related items

On 10/11/2024, in 21st century, 24x7x365 access, future, game-changing environment, Google, innovation, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, Open AI, platforms, podcasting, by Daniel Christian

The Future of Umpiring in Baseball: Balancing Tradition and Technology — from judgeschlegel.com by Judge Scott Schlegel
This article is not about baseball.

As we look to the future of umpiring in baseball, a balanced approach may offer the best solution. Rather than an all-or-nothing choice between human umpires and full automation, a hybrid system could potentially offer the benefits of both worlds. For instance, automated tracking systems could be used to assist human umpires, providing them with real-time data to inform their calls. This would maintain the human element and authority on the field while significantly enhancing accuracy and consistency.

Such a system would allow umpires to focus more on game management, player interactions, and the myriad other responsibilities that require human judgment and experience. It would preserve the traditional aspects of the umpire’s role that fans and players value, while leveraging technology to address concerns about accuracy and fairness.

Navigating the Intersection of Tradition and AI: The Future of Judicial Decision-Making — from judgeschlegel.com by Judge Scott Schlegel

Introduction
Continuing with our baseball analogy, we now turn our focus to the courtroom.

The intersection of technology and the justice system is a complex and often contentious space, much like the debate over automated umpires in baseball. As Major League Baseball considers whether automated systems should replace the human element in calling balls and strikes, the legal world faces similar questions: How far should we go in allowing technology to aid our decision-making processes, and what is the right balance between innovation and the traditions that define the courtroom?

AI and the rise of the Niche Lawyer — from jordanfurlong.substack.com by Jordan Furlong
A new legal market will create a new type of lawyer: Specialized, flexible, customized, fractional, home-based and online, exclusive, balanced and focused. This could be your future legal career.

Think of a new picture. A lawyer dressed in Professional Casual, or Business Comfortable, an outfit that looks sharp but feels relaxed. A lawyer inside their own apartment, in an extra bedroom, or in a shared workspace on a nearby bus route, taking an Uber to visit some clients and using Zoom to meet with others. A lawyer with a laptop and a tablet and a smartphone and no other capital expenditures. A lawyer whose overhead is only what’s literally over their head.

This lawyer starts work when they feel like it (maybe 7 am, maybe 10; maybe Monday, maybe not) and they stop working when they feel like it (maybe 4 pm, maybe 9). They have as many clients as they need, for whom they provide very specific, very personalized services. They provide some services that aren’t even “legal” to people who aren’t “clients” as we understand both terms. They have essential knowledge and skills that all lawyers share but unique knowledge and skills that hardly any others possess. They make as much money as they need in order to meet the rent and pay down their debts and afford a life with the people they love. They’re in complete charge of their career and their destiny, something they find terrifying and stressful and wonderful and fulfilling.

While We Were Distracted with the New ChatGPT Model, Google Quietly Dropped an AI Bombshell — from judgeschlegel.com by Judge Scott Schlegel

While the latest ChatGPT model is dominating tech headlines, I was unexpectedly blown away by Google’s recent release of a new NotebookLM feature: Audio Overview. This tool, which transforms written content into simulated conversations, caught me off guard with its capabilities. I uploaded some of my blog posts on AI and the justice system, and what it produced left me speechless. The AI generated podcast-like discussions felt remarkably authentic, complete with nuanced interpretations and even slight misunderstandings of my ideas. This mirrors real-life discussions perfectly – after all, how often do we hear our own thoughts expressed by others and think, “That’s not quite what I meant”?

? Breaking barriers isn’t just for athletes! Discover how Roger Bannister’s sub-4-minute mile can inspire a revolution in the justice system. ?? Read my latest article here: https://t.co/CCiWcqX6ri #schLegalTech #LegalTech pic.twitter.com/cjPCB4zM3b

— Judge Scott Schlegel (@Judgeschlegel) September 25, 2024

“185 real-world gen AI use cases from the world’s leading organizations” [Google], a professional network for AI agents [Shah] + other items re: AI in general

On 10/01/2024, in Artificial Intelligence/Agents/LLMs/and Related, business, cloud-based computing / apps / other cloud-related, communications, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, data related items, design, digital audio, digital video, emerging technologies, engineering, ethics, future, game-changing environment, Google, graphics, health, innovation, languages and translation, learning agents, Microsoft, morals/values, NVIDIA, online learning, online media, Open AI, platforms, podcasting, presentations, productivity / tips and tricks, programming, robotics, telemedicine / telehealth / virtual health, tools, training / L&D, United States, vendors, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

AI’s Trillion-Dollar Opportunity — from bain.com by David Crawford, Jue Wang, and Roy Singh
The market for AI products and services could reach between $780 billion and $990 billion by 2027.

At a Glance

The big cloud providers are the largest concentration of R&D, talent, and innovation today, pushing the boundaries of large models and advanced infrastructure.
Innovation with smaller models (open-source and proprietary), edge infrastructure, and commercial software is reaching enterprises, sovereigns, and research institutions.
Commercial software vendors are rapidly expanding their feature sets to provide the best use cases and leverage their data assets.

Accelerated market growth. Nvidia’s CEO, Jensen Huang, summed up the potential in the company’s Q3 2024 earnings call: “Generative AI is the largest TAM [total addressable market] expansion of software and hardware that we’ve seen in several decades.”

And on a somewhat related note (i.e., emerging technologies), also see the following two postings:

Surgical Robots: Current Uses and Future Expectations — from medicalfuturist.com by Pranavsingh Dhunnoo
As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called robotic surgeries or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre.

Key Takeaways

Robots’ potentials have been a fascination for humans and have even led to a booming field of robot-assisted surgery.
Surgical robots assist surgeons in performing accurate, minimally invasive procedures that are beneficial for patients’ recovery.
The assistance of robots extend beyond incisions and includes laparoscopies, radiosurgeries and, in the future, a combination of artificial intelligence technologies to assist surgeons in their craft.

Proto hologram tech allows cancer patients to receive specialist care without traveling large distances — from inavateonthenet.net

“Working with the team from Proto to bring to life, what several years ago would have seemed impossible, is now going to allow West Cancer Center & Research Institute to pioneer options for patients to get highly specialized care without having to travel to large metro areas,” said West Cancer’s CEO, Mitch Graves.

Google just got MASSIVE upgrade

Gemini is now inside Chrome

Here’re 7 Powerful Features you don’t want to miss: pic.twitter.com/XcCypnaKb0

— Poonam Soni (@CodeByPoonam) September 27, 2024

Obviously this workflow works just as well for meetings as it does for lectures. Stay present in the meeting with no screens and just write down the key points with pen and paper. Then let NotebookLM assemble the detailed summary based on your high-level notes. https://t.co/fZMG7LgsWG

— Steven Johnson (@stevenbjohnson) September 26, 2024

Clone your voice in minutes: The AI trick 95% don’t know about — from aidisruptor.ai by Alex McFarland
Warning: May cause unexpected bouts of talking to yourself

Now that you’ve got your voice clone, what can you do with it?

Content Creation:
- Podcast Production: Record episodes in half the time. Your listeners won’t know the difference, but your schedule will thank you.
- Audiobook Narration: Always wanted to narrate your own book? Now you can, without spending weeks in a recording studio.
- YouTube Videos: Create voiceovers for your videos in multiple languages. World domination, here you come!
Business Brilliance:
- Customer Service: Personalized automated responses that actually sound personal.
- Training Materials: Create engaging e-learning content in your own voice, minus the hours of recording.
- Presentations: Never worry about losing your voice before a big presentation again. Your clone’s got your back.

185 real-world gen AI use cases from the world’s leading organizations — from blog.google by Brian Hall; via Daniel Nest’s Why Try AI

In a matter of months, organizations have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes.

In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes, and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; code creation; data analysis; cybersecurity; and creative ideation and production.
…
Here’s a snapshot of how 185 of these industry leaders are putting AI to use today, creating real-world use cases that will transform tomorrow.

AI Data Drop: 3 Key Insights from Real-World Research on AI Usage — from microsoft.com; via Daniel Nest’s Why Try AI
One of the largest studies of Copilot usage—at nearly 60 companies—reveals how AI is changing the way we work.

AI is starting to liberate people from email
Meetings are becoming more about value creation
People are co-creating more with AI—and with one another

*** Dharmesh has been working on creating agent.ai — a professional network for AI agents.***

Speaking of agents, also see:

Onboarding the AI workforce: How digital agents will redefine work itself — from venturebeat.com by Gary Grossman

AI in 2030: A transformative force

AI agents are integral team members
The emergence of digital humans
AI-driven speech and conversational interfaces
AI-enhanced decision-making and leadership
Innovation and research powered by AI
The changing nature of job roles and skills

AI Video Tools You Can Use Today — from heatherbcooper.substack.com by Heather Cooper
The latest AI video models that deliver results

AI video models are improving so quickly, I can barely keep up! I wrote about unreleased Adobe Firefly Video in the last issue, and we are no closer to public access to Sora.

No worries – we do have plenty of generative AI video tools we can use right now.

Kling AI launched its updated v1.5 and the quality of image or text to video is impressive.
Hailuo MiniMax text to video remains free to use for now, and it produces natural and photorealistic results (with watermarks).
Runway added the option to upload portrait aspect ratio images to generate vertical videos in Gen-3 Alpha & Turbo modes.
…plus several more

Advanced Voice is rolling out to all Plus and Team users in the ChatGPT app over the course of the week.

While you’ve been patiently waiting, we’ve added Custom Instructions, Memory, five new voices, and improved accents.

It can also say “Sorry I’m late” in over 50 languages. pic.twitter.com/APOqqhXtDg

— OpenAI (@OpenAI) September 24, 2024

Should we be concerned about what’s happening at OpenAI? What does this say about the leader of arguably 1 of the most powerful co’s in the world today?

On 09/27/2024, in Artificial Intelligence/Agents/LLMs/and Related, business, change, changing business models, corporate / business world, Daniel S. Christian, future, game-changing environment, generational differences, global / globalization, leadership, new business models, Open AI, society, strategy, the downsides of how people use tech, United States, vendors, by Daniel Christian

One left
byu/jim_andr inOpenAI

From DSC:
I’m not trying to gossip here. I post this because Sam Altman is the head of arguably one of the most powerful companies in the world today — at least in terms of introducing change to a variety of societies throughout the globe (both positive and negative). So when we’ve now seen almost the entire leadership team head out the door, this certainly gives me major pause. I don’t like it. Items like the ones below begin to capture some of why I’m troubled and suspicious about these troubling moves.

OpenAI board mulls equity stake for Sam Altman that could be a massive payday — from fortune.com by Dave Smith
And as Linus Ekenstam points out:

So. hear me out. it’s natural for leadership to change. but if we look at Apple, leadership changes over decades if not more.

Why, if everything is so fast paced, hyper growth oriented and groundbreaking. Do people choose to leave?

I think I and many others are baffled

— Linus @ Meta Connect (@LinusEkenstam) September 26, 2024

OpenAI to Become For-Profit Company — from wsj.com by Deepa Seetharaman, Berber Jin, and Tom Dotan (behind paywall)
Planned restructuring comes amid personnel upheaval including resignation of chief technology officer
Three more execs out at OpenAI, including technology chief Mira Murati — from cnn.com by Clare Duffy
OpenAI’s executive exodus is continuing with three top leaders announcing their exits Wednesday, including Chief Technology Officer Mira Murati.

Learning Ecosystems

How far should we go in allowing technology to aid our decision-making processes? [Schlegel] + other legaltech-related items

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