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 AI-enhanced learning ecosystem” [Jennings] + other items re: AI in our learning ecosystems

The AI-enhanced learning ecosystem: A case study in collaborative innovation — from chieflearningofficer.com by Kevin Jennings
How artificial intelligence can serve as a tool and collaborative partner in reimagining content development and management.

Learning and development professionals face unprecedented challenges in today’s rapidly evolving business landscape. According to LinkedIn’s 2025 Workplace Learning Report, 67 percent of L&D professionals report being “maxed out” on capacity, while 66 percent have experienced budget reductions in the past year.

Despite these constraints, 87 percent agree their organizations need to develop employees faster to keep pace with business demands. These statistics paint a clear picture of the pressure L&D teams face: do more, with less, faster.

This article explores how one L&D leader’s strategic partnership with artificial intelligence transformed these persistent challenges into opportunities, creating a responsive learning ecosystem that addresses the modern demands of rapid product evolution and diverse audience needs. With 71 percent of L&D professionals now identifying AI as a high or very high priority for their learning strategy, this case study demonstrates how AI can serve not merely as a tool but as a collaborative partner in reimagining content development and management.
.


How we use GenAI and AR to improve students’ design skills — from timeshighereducation.com by Antonio Juarez, Lesly Pliego and Jordi Rábago who are professors of architecture at Monterrey Institute of Technology in Mexico; Tomas Pachajoa is a professor of architecture at the El Bosque University in Colombia; & Carlos Hinrichsen and Marietta Castro are educators at San Sebastián University in Chile.
Guidance on using generative AI and augmented reality to enhance student creativity, spatial awareness and interdisciplinary collaboration

Blend traditional skills development with AI use
For subjects that require students to develop drawing and modelling skills, have students create initial design sketches or models manually to ensure they practise these skills. Then, introduce GenAI tools such as Midjourney, Leonardo AI and ChatGPT to help students explore new ideas based on their original concepts. Using AI at this stage broadens their creative horizons and introduces innovative perspectives, which are crucial in a rapidly evolving creative industry.

Provide step-by-step tutorials, including both written guides and video demonstrations, to illustrate how initial sketches can be effectively translated into AI-generated concepts. Offer example prompts to demonstrate diverse design possibilities and help students build confidence using GenAI.

Integrating generative AI and AR consistently enhanced student engagement, creativity and spatial understanding on our course. 


How Texas is Preparing Higher Education for AI — from the74million.org by Kate McGee
TX colleges are thinking about how to prepare students for a changing workforce and an already overburdened faculty for new challenges in classrooms.

“It doesn’t matter if you enter the health industry, banking, oil and gas, or national security enterprises like we have here in San Antonio,” Eighmy told The Texas Tribune. “Everybody’s asking for competency around AI.”

It’s one of the reasons the public university, which serves 34,000 students, announced earlier this year that it is creating a new college dedicated to AI, cyber security, computing and data science. The new college, which is still in the planning phase, would be one of the first of its kind in the country. UTSA wants to launch the new college by fall 2025.

But many state higher education leaders are thinking beyond that. As AI becomes a part of everyday life in new, unpredictable ways, universities across Texas and the country are also starting to consider how to ensure faculty are keeping up with the new technology and students are ready to use it when they enter the workforce.


In the Room Where It Happens: Generative AI Policy Creation in Higher Education — from er.educause.edu by Esther Brandon, Lance Eaton, Dana Gavin, and Allison Papini

To develop a robust policy for generative artificial intelligence use in higher education, institutional leaders must first create “a room” where diverse perspectives are welcome and included in the process.


Q&A: Artificial Intelligence in Education and What Lies Ahead — from usnews.com by Sarah Wood
Research indicates that AI is becoming an essential skill to learn for students to succeed in the workplace.

Q: How do you expect to see AI embraced more in the future in college and the workplace?
I do believe it’s going to become a permanent fixture for multiple reasons. I think the national security imperative associated with AI as a result of competing against other nations is going to drive a lot of energy and support for AI education. We also see shifts across every field and discipline regarding the usage of AI beyond college. We see this in a broad array of fields, including health care and the field of law. I think it’s here to stay and I think that means we’re going to see AI literacy being taught at most colleges and universities, and more faculty leveraging AI to help improve the quality of their instruction. I feel like we’re just at the beginning of a transition. In fact, I often describe our current moment as the ‘Ask Jeeves’ phase of the growth of AI. There’s a lot of change still ahead of us. AI, for better or worse, it’s here to stay.




AI-Generated Podcasts Outperform Textbooks in Landmark Education Study — form linkedin.com by David Borish

A new study from Drexel University and Google has demonstrated that AI-generated educational podcasts can significantly enhance both student engagement and learning outcomes compared to traditional textbooks. The research, involving 180 college students across the United States, represents one of the first systematic investigations into how artificial intelligence can transform educational content delivery in real-time.


What can we do about generative AI in our teaching?  — from linkedin.com by Kristina Peterson

So what can we do?

  • Interrogate the Process: We can ask ourselves if we I built in enough checkpoints. Steps that can’t be faked. Things like quick writes, question floods, in-person feedback, revision logs.
  • Reframe AI: We can let students use AI as a partner. We can show them how to prompt better, revise harder, and build from it rather than submit it. Show them the difference between using a tool and being used by one.
  • Design Assignments for Curiosity, Not Compliance: Even the best of our assignments need to adapt. Mine needs more checkpoints, more reflective questions along the way, more explanation of why my students made the choices they did.

Teachers Are Not OK — from 404media.co by Jason Koebler

The response from teachers and university professors was overwhelming. In my entire career, I’ve rarely gotten so many email responses to a single article, and I have never gotten so many thoughtful and comprehensive responses.

One thing is clear: teachers are not OK.

In addition, universities are contracting with companies like Microsoft, Adobe, and Google for digital services, and those companies are constantly pushing their AI tools. So a student might hear “don’t use generative AI” from a prof but then log on to the university’s Microsoft suite, which then suggests using Copilot to sum up readings or help draft writing. It’s inconsistent and confusing.

I am sick to my stomach as I write this because I’ve spent 20 years developing a pedagogy that’s about wrestling with big ideas through writing and discussion, and that whole project has been evaporated by for-profit corporations who built their systems on stolen work. It’s demoralizing.

 

Google I/O 2025: From research to reality — from blog.google
Here’s how we’re making AI more helpful with Gemini.


Google I/O 2025 LIVE — all the details about Android XR smart glasses, AI Mode, Veo 3, Gemini, Google Beam and more — from tomsguide.com by Philip Michaels
Google’s annual conference goes all in on AI

With a running time of 2 hours, Google I/O 2025 leaned heavily into Gemini and new models that make the assistant work in more places than ever before. Despite focusing the majority of the keynote around Gemini, Google saved its most ambitious and anticipated announcement towards the end with its big Android XR smart glasses reveal.

Shockingly, very little was spent around Android 16. Most of its Android 16 related news, like the redesigned Material 3 Expressive interface, was announced during the Android Show live stream last week — which explains why Google I/O 2025 was such an AI heavy showcase.

That’s because Google carved out most of the keynote to dive deeper into Gemini, its new models, and integrations with other Google services. There’s clearly a lot to unpack, so here’s all the biggest Google I/O 2025 announcements.


Our vision for building a universal AI assistant— from blog.google
We’re extending Gemini to become a world model that can make plans and imagine new experiences by simulating aspects of the world.

Making Gemini a world model is a critical step in developing a new, more general and more useful kind of AI — a universal AI assistant. This is an AI that’s intelligent, understands the context you are in, and that can plan and take action on your behalf, across any device.

By applying LearnLM capabilities, and directly incorporating feedback from experts across the industry, Gemini adheres to the principles of learning science to go beyond just giving you the answer. Instead, Gemini can explain how you get there, helping you untangle even the most complex questions and topics so you can learn more effectively. Our new prompting guide provides sample instructions to see this in action.


Learn in newer, deeper ways with Gemini — from blog.google.com by Ben Gomes
We’re infusing LearnLM directly into Gemini 2.5 — plus more learning news from I/O.

At I/O 2025, we announced that we’re infusing LearnLM directly into Gemini 2.5, which is now the world’s leading model for learning. As detailed in our latest report, Gemini 2.5 Pro outperformed competitors on every category of learning science principles. Educators and pedagogy experts preferred Gemini 2.5 Pro over other offerings across a range of learning scenarios, both for supporting a user’s learning goals and on key principles of good pedagogy.


Gemini gets more personal, proactive and powerful — from blog.google.com by Josh Woodward
It’s your turn to create, learn and explore with an AI assistant that’s starting to understand your world and anticipate your needs.

Here’s what we announced at Google IO:

  • Gemini Live with camera and screen sharing, is now free on Android and iOS for everyone, so you can point your phone at anything and talk it through.
  • Imagen 4, our new image generation model, comes built in and is known for its image quality, better text rendering and speed.
  • Veo 3, our new, state-of-the-art video generation model, comes built in and is the first in the world to have native support for sound effects, background noises and dialogue between characters.
  • Deep Research and Canvas are getting their biggest updates yet, unlocking new ways to analyze information, create podcasts and vibe code websites and apps.
  • Gemini is coming to Chrome, so you can ask questions while browsing the web.
  • Students around the world can easily make interactive quizzes, and college students in the U.S., Brazil, Indonesia, Japan and the UK are eligible for a free school year of the Google AI Pro plan.
  • Google AI Ultra, a new premium plan, is for the pioneers who want the highest rate limits and early access to new features in the Gemini app.
  • 2.5 Flash has become our new default model, and it blends incredible quality with lightning fast response times.

Fuel your creativity with new generative media models and tools — from by Eli Collins
Introducing Veo 3 and Imagen 4, and a new tool for filmmaking called Flow.


AI in Search: Going beyond information to intelligence
We’re introducing new AI features to make it easier to ask any question in Search.

AI in Search is making it easier to ask Google anything and get a helpful response, with links to the web. That’s why AI Overviews is one of the most successful launches in Search in the past decade. As people use AI Overviews, we see they’re happier with their results, and they search more often. In our biggest markets like the U.S. and India, AI Overviews is driving over 10% increase in usage of Google for the types of queries that show AI Overviews.

This means that once people use AI Overviews, they’re coming to do more of these types of queries, and what’s particularly exciting is how this growth increases over time. And we’re delivering this at the speed people expect of Google Search — AI Overviews delivers the fastest AI responses in the industry.

In this story:

  • AI Mode in Search
  • Deep Search
  • Live capabilities
  • Agentic capabilities
  • Shopping
  • Personal context
  • Custom charts

 

 

The 2025 AI Index Report — from Stanford University’s Human-Centered Artificial Intelligence Lab (hai.stanford.edu); item via The Neuron

Top Takeaways

  1. AI performance on demanding benchmarks continues to improve.
  2. AI is increasingly embedded in everyday life.
  3. Business is all in on AI, fueling record investment and usage, as research continues to show strong productivity impacts.
  4. The U.S. still leads in producing top AI models—but China is closing the performance gap.
  5. The responsible AI ecosystem evolves—unevenly.
  6. Global AI optimism is rising—but deep regional divides remain.
  7. …and several more

Also see:

The Neuron’s take on this:

So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.

Just keep two big things in mind:

  1. Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
  2. Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.

So, use the tools, find what helps you, but don’t trust them completely.

We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.


Addendum on 4/16:

 




Students and folks looking for work may want to check out:

Also relevant/see:


 

The Best of AI 2024: Top Winners Across 9 Categories — from aiwithallie.beehiiv.com by Allie Miller
2025 will be our weirdest year in AI yet. Read this so you’re more prepared.


Top AI Tools of 2024 — from ai-supremacy.com by Michael Spencer (behind a paywall)
Which AI tools stood out for me in 2024? My list.

Memorable AI Tools of 2024
Catergories included:

  • Useful
  • Popular
  • Captures the zeighest of AI product innovation
  • Fun to try
  • Personally satisfying
  1. NotebookLM
  2. Perplexity
  3. Claude

New “best” AI tool? Really? — from theneurondaily.com by Noah and Grant
PLUS: A free workaround to the “best” new AI…

What is Google’s Deep Research tool, and is it really “the best” AI research tool out there?

Here’s how it works: Think of Deep Research as a research team that can simultaneously analyze 50+ websites, compile findings, and create comprehensive reports—complete with citations.

Unlike asking ChatGPT to research for you, Deep Research shows you its research plan before executing, letting you edit the approach to get exactly what you need.

It’s currently free for the first month (though it’ll eventually be $20/month) when bundled with Gemini Advanced. Then again, Perplexity is always free…just saying.

We couldn’t just take J-Cal’s word for it, so we rounded up some other takes:

Our take: We then compared Perplexity, ChatGPT Search, and Deep Research (which we’re calling DR, or “The Docta” for short) on robot capabilities from CES revealed:


An excerpt from today’s Morning Edition from Bloomberg

Global banks will cut as many as 200,000 jobs in the next three to five years—a net 3% of the workforce—as AI takes on more tasks, according to a Bloomberg Intelligence survey. Back, middle office and operations are most at risk. A reminder that Citi said last year that AI is likely to replace more jobs in banking than in any other sector. JPMorgan had a more optimistic view (from an employee perspective, at any rate), saying its AI rollout has augmented, not replaced, jobs so far.


 

 
 

1-800-CHAT-GPT—12 Days of OpenAI: Day 10

Per The Rundown: OpenAI just launched a surprising new way to access ChatGPT — through an old-school 1-800 number & also rolled out a new WhatsApp integration for global users during Day 10 of the company’s livestream event.


How Agentic AI is Revolutionizing Customer Service — from customerthink.com by Devashish Mamgain

Agentic AI represents a significant evolution in artificial intelligence, offering enhanced autonomy and decision-making capabilities beyond traditional AI systems. Unlike conventional AI, which requires human instructions, agentic AI can independently perform complex tasks, adapt to changing environments, and pursue goals with minimal human intervention.

This makes it a powerful tool across various industries, especially in the customer service function. To understand it better, let’s compare AI Agents with non-AI agents.

Characteristics of Agentic AI

    • Autonomy: Achieves complex objectives without requiring human collaboration.
    • Language Comprehension: Understands nuanced human speech and text effectively.
    • Rationality: Makes informed, contextual decisions using advanced reasoning engines.
    • Adaptation: Adjusts plans and goals in dynamic situations.
    • Workflow Optimization: Streamlines and organizes business workflows with minimal oversight.

Clio: A system for privacy-preserving insights into real-world AI use — from anthropic.com

How, then, can we research and observe how our systems are used while rigorously maintaining user privacy?

Claude insights and observations, or “Clio,” is our attempt to answer this question. Clio is an automated analysis tool that enables privacy-preserving analysis of real-world language model use. It gives us insights into the day-to-day uses of claude.ai in a way that’s analogous to tools like Google Trends. It’s also already helping us improve our safety measures. In this post—which accompanies a full research paper—we describe Clio and some of its initial results.


Evolving tools redefine AI video — from heatherbcooper.substack.com by Heather Cooper
Google’s Veo 2, Kling 1.6, Pika 2.0 & more

AI video continues to surpass expectations
The AI video generation space has evolved dramatically in recent weeks, with several major players introducing groundbreaking tools.

Here’s a comprehensive look at the current landscape:

  • Veo 2…
  • Pika 2.0…
  • Runway’s Gen-3…
  • Luma AI Dream Machine…
  • Hailuo’s MiniMax…
  • OpenAI’s Sora…
  • Hunyuan Video by Tencent…

There are several other video models and platforms, including …

 

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

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

Students also outlined their ideal active learning technologies:

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

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

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

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


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

Key Points

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

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

Microsoft has quietly built the largest enterprise AI agent ecosystem, with over 100,000 organizations creating or editing AI agents through its Copilot Studio since launch – a milestone that positions the company ahead in one of enterprise tech’s most closely watched and exciting  segments.

The rapid adoption comes as Microsoft significantly expands its agent capabilities. At its Ignite conference [that started on 11/19/24], the company announced it will allow enterprises to use any of the 1,800 large language models (LLMs) in the Azure catalog within these agents – a significant move beyond its exclusive reliance on OpenAI’s models. The company also unveiled autonomous agents that can work independently, detecting events and orchestrating complex workflows with minimal human oversight.


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

Along these lines, also see:


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

To understand the implications of AI agents, it’s useful to clarify the distinctions between AI, generative AI, and AI agents and explore the opportunities and risks they present to our autonomy, relationships, and decision-making.

AI Agents: These are specialized applications of AI designed to perform tasks or simulate interactions. AI agents can be categorized into:

    • Tool Agents…
    • Simulation Agents..

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

 

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

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

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

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

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

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



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

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

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

Now the math doesn’t look so simple.

Also see:

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

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

It’s called Lovable, the “world’s first AI fullstack engineer.”

Lovable does all of that by itself. Tell it what you want to build in plain English, and it creates everything you need. Want users to be able to log in? One click. Need to store data? One click. Want to accept payments? You get the idea.

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

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


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

Re: some ideas on how to use Notebook LM:

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

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

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


 

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

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

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

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.

 

Along these same lines, see:

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

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


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

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

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

This blog post demonstrates that it’s possible to leverage prompt injection to achieve, old school, command and control (C2) when giving novel AI systems access to computers.

We discussed one way to get malware onto a Claude Computer Use host via prompt injection. There are countless others, like another way is to have Claude write the malware from scratch and compile it. Yes, it can write C code, compile and run it. There are many other options.

TrustNoAI.

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

Also relevant here, see:


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


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

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


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

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

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


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

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

Top Generative AI Chatbots by Market Share – October 2024 


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

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

 

AI-governed robots can easily be hacked — 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/

 
© 2025 | Daniel Christian