the downsides of how people use tech

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

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

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

Introducing OpenAI for Government — from openai.com

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

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

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

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

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

Along these same lines, also see:

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

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

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

Claude’s response? Pure House of Cards:

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

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

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

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

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

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

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

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

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

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

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

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

Here’s how it works together:

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

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

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

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

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

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI [various authors]

On 06/20/2025, in Artificial Intelligence/Agents/LLMs/and Related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, liberal arts, memory, metacognition / metacognitive skills, participation, pedagogy, productivity / tips and tricks, psychology, research, student teaching/teacher education, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, youth, by Daniel Christian

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI — from papers.ssrn.com by Barbara Oakley, Michael Johnston, Kenzen Chen, Eulho Jung, and Terrence Sejnowski; via George Siemens

Abstract
In an era of generative AI and ubiquitous digital tools, human memory faces a paradox: the more we offload knowledge to external aids, the less we exercise and develop our own cognitive capacities. This chapter offers the first neuroscience-based explanation for the observed reversal of the Flynn Effect—the recent decline in IQ scores in developed countries—linking this downturn to shifts in educational practices and the rise of cognitive offloading via AI and digital tools. Drawing on insights from neuroscience, cognitive psychology, and learning theory, we explain how underuse of the brain’s declarative and procedural memory systems undermines reasoning, impedes learning, and diminishes productivity. We critique contemporary pedagogical models that downplay memorization and basic knowledge, showing how these trends erode long-term fluency and mental flexibility. Finally, we outline policy implications for education, workforce development, and the responsible integration of AI, advocating strategies that harness technology as a complement to – rather than a replacement for – robust human knowledge.

Keywords
cognitive offloading, memory, neuroscience of learning, declarative memory, procedural memory, generative AI, Flynn Effect, education reform, schemata, digital tools, cognitive load, cognitive architecture, reinforcement learning, basal ganglia, working memory, retrieval practice, schema theory, manifolds

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

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

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

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

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

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

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

Also see Meeker’s actual report at:

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

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

The details:

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

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

What could possibly go wrong with AI-based technological systems becoming “independent players?” [Christian]

On 06/04/2025, in Asia, biology, dangers of the status quo, emerging technologies, engineering, entrepreneurship, ethics, experimentation, health, human-computer interaction (HCI), ideas, innovation, morals/values, society, technology (general), the downsides of how people use tech, by Daniel Christian

Scientific breakthrough: artificial blood for all blood groups — from getsuperintel.com by Kim “Chubby” Isenberg
Japan’s universal artificial blood could revolutionize emergency medicine and global healthcare resilience.

They all show that we are on the threshold of a new era – one in which technological systems are no longer just tools, but independent players in medical, cognitive and infrastructural change.
…
This paradigm shift means that AI will no longer be limited to static training data, but will learn through open exploration, similar to biological organisms. This is nothing less than the beginning of an era of autonomous cognition.

From DSC:
While there are some promising developments involving AI these days, we need to look at what the potential downsides might be of AI becoming independent players, don’t you think? Otherwise, what could possibly go wrong?

“Rise of AI-generated deepfake videos spreads misinformation” [iblnews.org] + “New tools for ultimate character consistency” [Cooper] + more

On 05/13/2025, in Artificial Intelligence/Agents/LLMs/and Related, creativity, digital video, media/film, social media, society, the downsides of how people use tech, tools, vendors, by Daniel Christian

New tools for ultimate character consistency — from heatherbcooper.substack.com by Heather B. Cooper
Plus simple & effective video prompt tips

We have some new tools for character, objects, and scene consistency with Runway and Midjourney.

Multimodal AI = multi-danger — from theneurondaily.com by Grant Harvey

According to a new report from Enkrypt AI, multimodal models have opened the door to sneakier attacks (like Ocean’s Eleven, but with fewer suits and more prompt injections).

Naturally, Enkrypt decided to run a few experiments… and things escalated quickly.

They tested two of Mistral’s newest models—Pixtral-Large and Pixtral-12B, built to handle words and visuals.

What they found? Yikes:

- The models are 40x more likely to generate dangerous chemical / biological / nuclear info.
- And 60x more likely to produce child sexual exploitation material compared to top models like OpenAI’s GPT-4o or Anthropic’s Claude 3.7 Sonnet.

Rise of AI-generated deepfake videos spreads misinformation — from iblnews.org

This technology could easily be abused and lock people out of almost anything. [Christian]

On 05/02/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, business side of he, cryptocurrencies, Daniel S. Christian, economics, global / globalization, society, the downsides of how people use tech, tools, United States, by Daniel Christian

Sam Altman’s Eye-Scanning Orb Is Now Coming to the US — from wired.com by Lauren Goode
At a buzzy event in San Francisco, World announced a series of Apple-like stores, a partnership with dating giant Match Group, and a new mini gadget to scan your eyeballs.

The device-and-app combo scans people’s irises, creates a unique user ID, stores that information on the blockchain, and uses it as a form of identity verification. If enough people adopt the app globally, the thinking goes, it could ostensibly thwart scammers.
…
The bizarre identity verification process requires that users get their eyeballs scanned, so Tools for Humanity is expanding its physical footprint to make that a possibility.
…
But World is also a for-profit cryptocurrency company that wants to build a borderless, “globally inclusive” financial network. And its approach has been criticized by privacy advocates and regulators. In its early days, World was explicitly marketing its services to countries with a high percentage of unbanked or underbanked citizens, and offering free crypto as an incentive for people to sign up and have their irises scanned.

From DSC:
If people and governments could be trusted with the level of power a global ID network/service could bring, this could be a great technology. But I could easily see it being abused. Heck, even our own President doesn’t listen to the Judicial Branch of our government! He’s in contempt of court, essentially. But he doesn’t seem to care.

“How People Are Really Using Gen AI in 2025” [Zao-Sanders] + other items re: AI

On 04/17/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business, corporate / business world, creativity, education, emerging technologies, learning, learning agents, platforms, productivity / tips and tricks, relationships, research, society, the downsides of how people use tech, workplace, by Daniel Christian

How People Are Really Using Gen AI in 2025 — from hbr.org by Marc Zao-Sanders

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Here’s why you shouldn’t let AI run your company… — from theneurondaily.com by Grant Harvey; emphasis DSC

When “vibe-coding” goes wrong… or, a parable in why you shouldn’t “vibe” your entire company.
Cursor, an AI-powered coding tool that many developers love-to-hate, face-planted spectacularly yesterday when its own AI support bot went off-script and fabricated a company policy, leading to a complete user revolt.

Here’s the short version:

A bug locked Cursor users out when switching devices.
Instead of human help, Cursor’s AI support bot confidently told users this was a new policy (it wasn’t).
No human checked the replies—big mistake.
The fake news spread, and devs canceled subscriptions en masse.
A Reddit thread about it got mysteriously nuked, fueling suspicion.

The reality? Just a bug, plus a bot hallucination… doing maximum damage.
…
Why it matters: This is what we’d call “vibe-companying”—blindly trusting AI with critical functions without human oversight.

Think about it like this: this was JUST a startup. If more big corporations continue to lay off entire departments, replaced by AI, these already byzantine companies will become increasingly more opaque, unaccountable systems where no one, human or AI, fully understands what’s happening or who’s responsible.

Our take? Kafka dude has it right. We need to pay attention to WHAT we’re actually automating. Because automating more bureaucracy at scale, with agents we increasingly don’t understand or don’t double check, can potentially make companies less intelligent—and harder to fix when things inevitably go wrong.

Outsourcing Thought: The Hidden Cost of Letting AI Think for You — from linkedin.com by Robert Atkinson

I’ve watched it unfold in real time. A student submits a flawless coding assignment or a beautifully written essay—clean syntax, sharp logic, polished prose. But when I ask them to explain their thinking, they hesitate. They can’t trace their reasoning or walk me through the process. The output is strong, but the understanding is shallow. As a professor, I’ve seen this pattern grow more common: AI-assisted work that looks impressive on the surface but reveals a troubling absence of cognitive depth underneath.

This article is written with my students in mind—but it’s meant for anyone navigating learning, teaching, or thinking in the age of artificial intelligence. Whether you’re a student, educator, or professional, the question is the same: What happens to the brain when we stop doing our own thinking?

We are standing at a pivotal moment. With just a few prompts, generative AI can produce essays, solve complex coding problems, and summarize ideas in seconds. It feels efficient. It feels like progress. But from a cognitive neuroscience perspective, that convenience comes at a hidden cost: the gradual erosion of the neural processes that support reasoning, creativity, and long-term learning.

Like it or not, AI is learning how to influence you — from venturebeat.com by Louis Rosenberg

Unfortunately, without regulatory protections, we humans will likely become the objective that AI agents are tasked with optimizing.

I am most concerned about the conversational agents that will engage us in friendly dialog throughout our daily lives. They will speak to us through photorealistic avatars on our PCs and phones and soon, through AI-powered glasses that will guide us through our days. Unless there are clear restrictions, these agents will be designed to conversationally probe us for information so they can characterize our temperaments, tendencies, personalities and desires, and use those traits to maximize their persuasive impact when working to sell us products, pitch us services or convince us to believe misinformation.
.

“Over 100 AI Tools for Teachers” [Kharbach] + other items re: AI in our learning ecosystems

On 02/01/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, platforms, productivity / tips and tricks, student-related, teachers, teaching & learning, teaching online, technologies for your home, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, vendors, by Daniel Christian

DeepSeek: How China’s AI Breakthrough Could Revolutionize Educational Technology — from nickpotkalitsky.substack.com by Nick Potkalitsky
Can DeepSeek’s 90% efficiency boost make AI accessible to every school?

The most revolutionary aspect of DeepSeek for education isn’t just its cost—it’s the combination of open-source accessibility and local deployment capabilities. As Azeem Azhar notes, “R-1 is open-source. Anyone can download and run it on their own hardware. I have R1-8b (the second smallest model) running on my Mac Mini at home.”
…

Real-time Learning Enhancement

AI tutoring networks that collaborate to optimize individual learning paths
Immediate, multi-perspective feedback on student work
Continuous assessment and curriculum adaptation

The question isn’t whether this technology will transform education—it’s how quickly institutions can adapt to a world where advanced AI capabilities are finally within reach of every classroom.

Over 100 AI Tools for Teachers — from educatorstechnology.com by Med Kharbach, PhD

I know through your feedback on my social media and blog posts that several of you have legitimate concerns about the impact of AI in education, especially those related to data privacy, academic dishonesty, AI dependence, loss of creativity and critical thinking, plagiarism, to mention a few. While these concerns are valid and deserve careful consideration, it’s also important to explore the potential benefits AI can bring when used thoughtfully.

Tools such as ChatGPT and Claude are like smart research assistants that are available 24/7 to support you with all kinds of tasks from drafting detailed lesson plans, creating differentiated materials, generating classroom activities, to summarizing and simplifying complex topics. Likewise, students can use them to enhance their learning by, for instance, brainstorming ideas for research projects, generating constructive feedback on assignments, practicing problem-solving in a guided way, and much more.

The point here is that AI is here to stay and expand, and we better learn how to use it thoughtfully and responsibly rather than avoid it out of fear or skepticism.

Beth’s posting links to:

Digital Education Council Global AI Faculty Survey 2025 — from digitaleducationcouncil.com

Derek’s posting on LinkedIn

From Theory to Practice: How Generative AI is Redefining Instructional Materials — from edtechinsiders.substack.com by Alex Sarlin
Top trends and insights from The Edtech Insiders Generative AI Map research process about how Generative AI is transforming Instructional Materials

As part of our updates to the Edtech Insiders Generative AI Map, we’re excited to release a new mini market map and article deep dive on Generative AI tools that are specifically designed for Instructional Materials use cases.

In our database, the Instructional Materials use case category encompasses tools that:

Assist educators by streamlining lesson planning, curriculum development, and content customization
Enable educators or students to transform materials into alternative formats, such as videos, podcasts, or other interactive media, in addition to leveraging gaming principles or immersive VR to enhance engagement
Empower educators or students to transform text, video, slides or other source material into study aids like study guides, flashcards, practice tests, or graphic organizers
Engage students through interactive lessons featuring historical figures, authors, or fictional characters
Customize curriculum to individual needs or pedagogical approaches
Empower educators or students to quickly create online learning assets and courses

On a somewhat-related note, also see:

Tech & Learning Announces Winners of Best of 2024 — from techlearning.com by TL Editors
This annual award celebrates recognizing the best in EdTech from 2024

NVIDIA’s Apple moment?! — from theneurondaily.com by Noah Edelman and Grant Harvey
PLUS: How to level up your AI workflows for 2025…

NVIDIA wants to put an AI supercomputer on your desk (and it only costs $3,000).
…
And last night at CES 2025, Jensen Huang announced phase two of this plan: Project DIGITS, a $3K personal AI supercomputer that runs 200B parameter models from your desk. Guess we now know why Apple recently developed an NVIDIA allergy…
…
But NVIDIA doesn’t just want its “Apple PC moment”… it also wants its OpenAI moment. NVIDIA also announced Cosmos, a platform for building physical AI (think: robots and self-driving cars)—which Jensen Huang calls “the ChatGPT moment for robotics.”

Jensen Huang’s latest CES speech: AI Agents are expected to become the next robotics industry, with a scale reaching trillions of dollars — from chaincatcher.com

NVIDIA is bringing AI from the cloud to personal devices and enterprises, covering all computing needs from developers to ordinary users.

At CES 2025, which opened this morning, NVIDIA founder and CEO Jensen Huang delivered a milestone keynote speech, revealing the future of AI and computing. From the core token concept of generative AI to the launch of the new Blackwell architecture GPU, and the AI-driven digital future, this speech will profoundly impact the entire industry from a cross-disciplinary perspective.

Also see:

NVIDIA Project DIGITS: The World’s Smallest AI Supercomputer. — from nvidia.com
A Grace Blackwell AI Supercomputer on your desk.

From DSC:
I’m posting this next item (involving Samsung) as it relates to how TVs continue to change within our living rooms. AI is finding its way into our TVs…the ramifications of this remain to be seen.

OpenAI ‘now knows how to build AGI’ — from therundown.ai by Rowan Cheung
PLUS: AI phishing achieves alarming success rates

The Rundown: Samsung revealed its new “AI for All” tagline at CES 2025, introducing a comprehensive suite of new AI features and products across its entire ecosystem — including new AI-powered TVs, appliances, PCs, and more.

The details:

Vision AI brings features like real-time translation, the ability to adapt to user preferences, AI upscaling, and instant content summaries to Samsung TVs.
Several of Samsung’s new Smart TVs will also have Microsoft Copilot built in, while also teasing a potential AI partnership with Google.
Samsung also announced the new line of Galaxy Book5 AI PCs, with new capabilities like AI-powered search and photo editing.
AI is also being infused into Samsung’s laundry appliances, art frames, home security equipment, and other devices within its SmartThings ecosystem.

Why it matters: Samsung’s web of products are getting the AI treatment — and we’re about to be surrounded by AI-infused appliances in every aspect of our lives. The edge will be the ability to sync it all together under one central hub, which could position Samsung as the go-to for the inevitable transition from smart to AI-powered homes.

***

“Samsung sees TVs not as one-directional devices for passive consumption but as interactive, intelligent partners that adapt to your needs,” said SW Yong, President and Head of Visual Display Business at Samsung Electronics. “With Samsung Vision AI, we’re reimagining what screens can do, connecting entertainment, personalization, and lifestyle solutions into one seamless experience to simplify your life.” — from Samsung

Understanding And Preparing For The 7 Levels Of AI Agents — from forbes.com by Douglas B. Laney

The following framework I offer for defining, understanding, and preparing for agentic AI blends foundational work in computer science with insights from cognitive psychology and speculative philosophy. Each of the seven levels represents a step-change in technology, capability, and autonomy. The framework expresses increasing opportunities to innovate, thrive, and transform in a data-fueled and AI-driven digital economy.

The Rise of AI Agents and Data-Driven Decisions — from devprojournal.com by Mike Monocello
Fueled by generative AI and machine learning advancements, we’re witnessing a paradigm shift in how businesses operate and make decisions.

AI Agents Enhance Generative AI’s Impact
Burley Kawasaki, Global VP of Product Marketing and Strategy at Creatio, predicts a significant leap forward in generative AI. “In 2025, AI agents will take generative AI to the next level by moving beyond content creation to active participation in daily business operations,” he says. “These agents, capable of partial or full autonomy, will handle tasks like scheduling, lead qualification, and customer follow-ups, seamlessly integrating into workflows. Rather than replacing generative AI, they will enhance its utility by transforming insights into immediate, actionable outcomes.”

Here’s what nobody is telling you about AI agents in 2025 — from aidisruptor.ai by Alex McFarland
What’s really coming (and how to prepare).

Everyone’s talking about the potential of AI agents in 2025 (and don’t get me wrong, it’s really significant), but there’s a crucial detail that keeps getting overlooked: the gap between current capabilities and practical reliability.

Here’s the reality check that most predictions miss: AI agents currently operate at about 80% accuracy (according to Microsoft’s AI CEO). Sounds impressive, right? But here’s the thing – for businesses and users to actually trust these systems with meaningful tasks, we need 99% reliability. That’s not just a 19% gap – it’s the difference between an interesting tech demo and a business-critical tool.

This matters because it completely changes how we should think about AI agents in 2025. While major players like Microsoft, Google, and Amazon are pouring billions into development, they’re all facing the same fundamental challenge – making them work reliably enough that you can actually trust them with your business processes.

Think about it this way: Would you trust an assistant who gets things wrong 20% of the time? Probably not. But would you trust one who makes a mistake only 1% of the time, especially if they could handle repetitive tasks across your entire workflow? That’s a completely different conversation.

Why 2025 will be the year of AI orchestration — from venturebeat.com by Emilia David|

In the tech world, we like to label periods as the year of (insert milestone here). This past year (2024) was a year of broader experimentation in AI and, of course, agentic use cases.

As 2025 opens, VentureBeat spoke to industry analysts and IT decision-makers to see what the year might bring. For many, 2025 will be the year of agents, when all the pilot programs, experiments and new AI use cases converge into something resembling a return on investment.

In addition, the experts VentureBeat spoke to see 2025 as the year AI orchestration will play a bigger role in the enterprise. Organizations plan to make management of AI applications and agents much more straightforward.

Here are some themes we expect to see more in 2025.

Predictions For AI In 2025: Entrepreneurs Look Ahead — from forbes.com by Jodie Cook

AI agents take charge
Jérémy Grandillon, CEO of TC9 – AI Allbound Agency, said “Today, AI can do a lot, but we don’t trust it to take actions on our behalf. This will change in 2025. Be ready to ask your AI assistant to book a Uber ride for you.” Start small with one agent handling one task. Build up to an army.

“If 2024 was agents everywhere, then 2025 will be about bringing those agents together in networks and systems,” said Nicholas Holland, vice president of AI at Hubspot. “Micro agents working together to accomplish larger bodies of work, and marketplaces where humans can ‘hire’ agents to work alongside them in hybrid teams. Before long, we’ll be saying, ‘there’s an agent for that.'”
…
Voice becomes default
Stop typing and start talking. Adam Biddlecombe, head of brand at Mindstream, predicts a shift in how we interact with AI. “2025 will be the year that people start talking with AI,” he said. “The majority of people interact with ChatGPT and other tools in the text format, and a lot of emphasis is put on prompting skills.

Biddlecombe believes, “With Apple’s ChatGPT integration for Siri, millions of people will start talking to ChatGPT. This will make AI so much more accessible and people will start to use it for very simple queries.”

Get ready for the next wave of advancements in AI. AGI arrives early, AI agents take charge, and voice becomes the norm. Video creation gets easy, AI embeds everywhere, and one-person billion-dollar companies emerge.

These 4 graphs show where AI is already impacting jobs — from fastcompany.com by Brandon Tucker
With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce.

To better understand the types of roles that AI is impacting, ZoomInfo’s research team looked to its proprietary database of professional contacts for answers. The platform, which detects more than 1.5 million personnel changes per day, revealed a dramatic increase in AI-related job titles since 2022. With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce.

Why does this shift in AI titles matter for every industry?

“5 Ways Teachers Can Use NotebookLM Today” [Burns} + other items re: AI in our learning ecosystems

On 12/29/2024, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Australia, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital audio, digital learning, digital video, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, United States, universities, vendors, vision/possibilities, by Daniel Christian

How AI Is Changing Education: The Year’s Top 5 Stories — from edweek.org by Alyson Klein

Ever since a new revolutionary version of chat ChatGPT became operable in late 2022, educators have faced several complex challenges as they learn how to navigate artificial intelligence systems.
…
Education Week produced a significant amount of coverage in 2024 exploring these and other critical questions involving the understanding and use of AI.

Here are the five most popular stories that Education Week published in 2024 about AI in schools.

What’s next with AI in higher education? — from msn.com by Science X Staff

Dr. Lodge said there are five key areas the higher education sector needs to address to adapt to the use of AI:

1. Teach ‘people’ skills as well as tech skills
2. Help all students use new tech
3. Prepare students for the jobs of the future
4. Learn to make sense of complex information
5. Universities to lead the tech change

5 Ways Teachers Can Use NotebookLM Today — from classtechtips.com by Dr. Monica Burns

Introducing Gemini 2.0: our new AI model for the agentic era — from blog.google by Sundar Pichai, Demis Hassabis, and Koray Kavukcuoglu

Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.

We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.

Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.

.

Try Deep Research and our new experimental model in Gemini, your AI assistant — from blog.google by Dave Citron
Deep Research rolls out to Gemini Advanced subscribers today, saving you hours of time. Plus, you can now try out a chat optimized version of 2.0 Flash Experimental in Gemini on the web.

Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.

Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1

Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.

Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.
…
Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.

Gemini 2.0 is the next chapter for Google AI — from axios.com by Ina Fried

Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…
…
The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.

“We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
“If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.

AI Agents vs. AI Assistants: Know the Key Differences — from aithority.com by Rishika Patel

The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.

Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.

Discover how to accelerate AI transformation with NVIDIA and Microsoft — from ignite.microsoft.com

Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.

Google + Meta + Apple New AI — from theneurondaily.com by Grant Harve

What else Google announced:

Deep Research: New feature that can explore topics and compile reports.
Project Astra: AI agent that can use Google Search, Lens, and Maps, understands multiple languages, and has 10-minute conversation memory.
Project Mariner: A browser control agent that can complete web tasks (83.5% success rate on WebVoyager benchmark). Read more about Mariner here.
Agents to help you play (or test) video games.

AI Agents: Easier To Build, Harder To Get Right — from forbes.com by Andres Zunino

The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.

The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.

“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.

(Excerpt from the 12/4/24 edition)

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

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

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

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

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

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

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

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

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

Here’s what you need to know:

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

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

Also related, see:

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

From World Labs

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

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

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

Addendum on 12/5/24:

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

Learning Ecosystems

What could possibly go wrong with AI-based technological systems becoming “independent players?” [Christian]

5 items re: AI in general

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