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“Miscommunication Leads AI-Based Hiring Tools Astray” [adigaskell.org] + other items re: AI in general

On 11/19/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, Blockchain, computer science, design, emerging technologies, engineering, experimentation, game-changing environment, Google, graphics, India, innovation, Microsoft, NVIDIA, Open AI, platforms, programming, robotics, simulations, society, tools, usability, user experience (UX), vendors, by Daniel Christian

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:

  1. DALL-E 3 by OpenAI (via Microsoft Designer)
  2. FLUX1.1 [pro] by Black Forest Labs (via Glif)
  3. Ideogram 2.0 by Ideogram (via Ideogram)
  4. Imagen 3 by Google (via Image FX)
  5. Midjourney 6.1 by Midjourney (via Midjourney)
  6. Recraft V3 by Recraft (via Recraft)
  7. 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.

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“Using AI as an exploratory tool for investigation, interrogation, & intellectual discovery” [Spencer & Potkalitsky] + other items re: AI in our LEs

On 11/07/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, colleges, community colleges, education technology, emerging technologies, higher education, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, teaching & learning, the downsides of how people use tech, tools, trends, UK, United States, universities, vendors, by Daniel Christian

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.

  1. Understand the impact…
  2. Understand the different types of AI tools…
  3. 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:

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:

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.

 

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“Introducing ChatGPT search” [OpenAI] + other items re: AI in general

On 11/01/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business, change, changing business models, cloud-based computing / apps / other cloud-related, communities of practice, emerging technologies, Google, human-computer interaction (HCI), India, innovation, intelligent systems, NVIDIA, Open AI, platforms, society, tools, United States, vendors, workplace, by Daniel Christian

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.

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.

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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 / Machine Learning / Deep Learning / Algorithms, 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

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.

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“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 / Machine Learning / Deep Learning / Algorithms, 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:

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:

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/

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Several items re: AI in our learning ecosystems

On 10/18/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, digital audio, digital learning, education technology, emerging technologies, experimentation, faculty, Google, higher education, human-computer interaction (HCI), ideas, instructional design, learning ecosystem, Learning Experience Design, multimedia, online learning, online media, Open AI, teaching & learning, tools, United States, universities, vendors, by Daniel Christian

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.

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A variety of items re: AI in our learning ecosystems

On 10/14/2024, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty, future, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, learning ecosystem, Learning Experience Design, Open AI, training / L&D, United States, universities, by Daniel Christian

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?

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The state of AI; using AI to buy a home; introducing canvas; + other items re: AI in general

On 10/14/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, bots, business, Canvas - and other Instructure-related items, cloud-based computing / apps / other cloud-related, collaboration, economics, future, game-changing environment, NVIDIA, Open AI, political science, productivity / tips and tricks, programming, science, society, sociology, tools, vision/possibilities, web-based collaboration, workplace, writing, by Daniel Christian

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.”

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.
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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”?

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“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 / Machine Learning / Deep Learning / Algorithms, 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.

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?

  1. 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!
  2. 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.

  1. AI is starting to liberate people from email
  2. Meetings are becoming more about value creation
  3. 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

  1. AI agents are integral team members
  2. The emergence of digital humans
  3. AI-driven speech and conversational interfaces
  4. AI-enhanced decision-making and leadership
  5. Innovation and research powered by AI
  6. 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

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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 / Machine Learning / Deep Learning / Algorithms, 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.

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“AI, Humans and Work: 10 Thoughts.” [Tobaccowala] + other items re: AI in general

On 09/23/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, change, creativity, emerging technologies, engineering, experimentation, future, game-changing environment, generational differences, media/film, Open AI, platforms, robotics, society, tools, United States, vendors, workplace, by Daniel Christian

AI researcher Jim Fan has had a charmed career. He was OpenAI’s first intern before he did his PhD at Stanford with “godmother of AI,” Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI “GEAR” group. The lab’s current work spans foundation models for humanoid robots to agents for virtual worlds. Jim describes a three-pronged data strategy for robotics, combining internet-scale data, simulation data and real world robot data. He believes that in the next few years it will be possible to create a “foundation agent” that can generalize across skills, embodiments and realities—both physical and virtual. He also supports Jensen Huang’s idea that “Everything that moves will eventually be autonomous.”

Runway Partners with Lionsgate — from runwayml.com via The Rundown AI
Runway and Lionsgate are partnering to explore the use of AI in film production.

Lionsgate and Runway have entered into a first-of-its-kind partnership centered around the creation and training of a new AI model, customized on Lionsgate’s proprietary catalog. Fundamentally designed to help Lionsgate Studios, its filmmakers, directors and other creative talent augment their work, the model generates cinematic video that can be further iterated using Runway’s suite of controllable tools.

Per The Rundown: Lionsgate, the film company behind The Hunger Games, John Wick, and Saw, teamed up with AI video generation company Runway to create a custom AI model trained on Lionsgate’s film catalogue.

The details:

  • The partnership will develop an AI model specifically trained on Lionsgate’s proprietary content library, designed to generate cinematic video that filmmakers can further manipulate using Runway’s tools.
  • Lionsgate sees AI as a tool to augment and enhance its current operations, streamlining both pre-production and post-production processes.
  • Runway is considering ways to offer similar custom-trained models as templates for individual creators, expanding access to AI-powered filmmaking tools beyond major studios.

Why it matters: As many writers, actors, and filmmakers strike against ChatGPT, Lionsgate is diving head-first into the world of generative AI through its partnership with Runway. This is one of the first major collabs between an AI startup and a major Hollywood company — and its success or failure could set precedent for years to come.

A bottle of water per email: the hidden environmental costs of using AI chatbots — from washingtonpost.com by Pranshu Verma and Shelly Tan (behind paywall)
AI bots generate a lot of heat, and keeping their computer servers running exacts a toll.

Each prompt on ChatGPT flows through a server that runs thousands of calculations to determine the best words to use in a response.

In completing those calculations, these servers, typically housed in data centers, generate heat. Often, water systems are used to cool the equipment and keep it functioning. Water transports the heat generated in the data centers into cooling towers to help it escape the building, similar to how the human body uses sweat to keep cool, according to Shaolei Ren, an associate professor at UC Riverside.

Where electricity is cheaper, or water comparatively scarce, electricity is often used to cool these warehouses with large units resembling air-conditioners, he said. That means the amount of water and electricity an individual query requires can depend on a data center’s location and vary widely.

AI, Humans and Work: 10 Thoughts. — from rishad.substack.com by Rishad Tobaccowala
The Future Does Not Fit in the Containers of the Past. Edition 215.

10 thoughts about AI, Humans and Work in 10 minutes:

  1. AI is still Under-hyped.
  2. AI itself will be like electricity and is unlikely to be a differentiator for most firms.
  3. AI is not alive but can be thought of as a new species.
  4. Knowledge will be free and every knowledge workers job will change in 2025.
  5. The key about AI is not to ask what AI will do to us but what AI can do for us.
  6. Plus 5 other thoughts

 

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Numerous items re: OpenAI o1, Microsoft Copilot, Google’s Notebook LM, and AI in general

On 09/17/2024, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, education technology, emerging technologies, Google, innovation, Microsoft, Open AI, platforms, productivity / tips and tricks, skills, tools, United States, by Daniel Christian

“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?
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“Introducing OpenAI o1” [OpenAI] + other items re: AI in general

On 09/12/2024, in Adobe, art, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, creativity, digital audio, digital learning, digital storytelling, digital video, education, education technology, emerging technologies, experimentation, Google, graphics, multimedia, new media literacies, online media, Open AI, physics, platforms, productivity / tips and tricks, tools, training / L&D, trends, vendors, by Daniel Christian

Introducing OpenAI o1 – from openai.com

We’ve developed a new series of AI models designed to spend more time thinking before they respond. Here is the latest news on o1 research, product and other updates.

Something New: On OpenAI’s “Strawberry” and Reasoning — from oneusefulthing.org by Ethan Mollick
Solving hard problems in new ways

The new AI model, called o1-preview (why are the AI companies so bad at names?), lets the AI “think through” a problem before solving it. This lets it address very hard problems that require planning and iteration, like novel math or science questions. In fact, it can now beat human PhD experts in solving extremely hard physics problems.

To be clear, o1-preview doesn’t do everything better. It is not a better writer than GPT-4o, for example. But for tasks that require planning, the changes are quite large.

What is the point of Super Realistic AI? — from Heather Cooper who runs Visually AI on Substack

The arrival of super realistic AI image generation, powered by models like Midjourney, FLUX.1, and Ideogram, is transforming the way we create and use visual content.

Recently, many creators (myself included) have been exploring super realistic AI more and more.

But where can this actually be used?

Super realistic AI image generation will have far-reaching implications across various industries and creative fields. Its importance stems from its ability to bridge the gap between imagination and visual representation, offering multiple opportunities for innovation and efficiency.

Heather goes on to mention applications in:

  • Creative Industries
  • Entertainment and Media
  • Education and Training

NotebookLM now lets you listen to a conversation about your sources — from blog.google by Biao Wang
Our new Audio Overview feature can turn documents, slides, charts and more into engaging discussions with one click.

Today, we’re introducing Audio Overview, a new way to turn your documents into engaging audio discussions. With one click, two AI hosts start up a lively “deep dive” discussion based on your sources. They summarize your material, make connections between topics, and banter back and forth. You can even download the conversation and take it on the go.

Bringing generative AI to video with Adobe Firefly Video Model — from blog.adobe.com by Ashley Still

Over the past several months, we’ve worked closely with the video editing community to advance the Firefly Video Model. Guided by their feedback and built with creators’ rights in mind, we’re developing new workflows leveraging the model to help editors ideate and explore their creative vision, fill gaps in their timeline and add new elements to existing footage.

Just like our other Firefly generative AI models, editors can create with confidence knowing the Adobe Firefly Video Model is designed to be commercially safe and is only trained on content we have permission to use — never on Adobe users’ content.

We’re excited to share some of the incredible progress with you today — all of which is designed to be commercially safe and available in beta later this year. To be the first to hear the latest updates and get access, sign up for the waitlist here.

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“Which AI tools do Instructional Designers use the most?” [Hardman] + other items re: AI in our learning ecosystems

On 09/12/2024, in 21st century, accessibility / UDL, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, biology, colleges, community colleges, corporate universities / corporate training, creativity, digital audio, digital learning, digital video, education technology, emerging technologies, experimentation, face-to-face, faculty, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, learning, learning ecosystem, Learning Experience Design, media/film, multimedia, Natural Language Processing (NLP), neurodivergent/special needs, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, voice recognition / voice enabled interfaces, writing, by Daniel Christian

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.

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