9 Creative ways to use ChatGPT, ChatGPT’s new Study Mode, AI models may be learning each others’ bad behaviors, How jobs will be impacted by AI, How AI is “tearing apart companies”, How to shape your Gen AI strategy, Sam Altman warns there’s no right to privacy when using ChatGPT, the U.S. is sending AI drone kits to Ukraine, China wants a global approach to AI, and more, so…
AI Tips & Tricks
9 creative ways to use ChatGPT that are outside the box
(MRM - Summarized by AI)
Simulate potential outcomes of scenarios – Explore “what-if” scenarios (real or fantasy), like reunified Korea or half the world vanishing, and see how ChatGPT narrates likely consequences.
Explore historical what‑ifs – Ask ChatGPT what might have happened if major historical events had gone differently (e.g. Axis won WWII, Roman Empire never collapsed).
Chat with fictional characters – Role-play conversations with characters like Superman or Mickey Mouse, discussing their fictional lives and perspectives.
Play an interactive text adventure – Have ChatGPT act as a choose-your-own-adventure engine, narrating a story and letting you make decisions in real time
Generate characters for stories or Dungeons & Dragons – Provide basic details and have ChatGPT build full character profiles for storytelling or tabletop play.
Debate two sides of an argument – Request ChatGPT to present balanced pros and cons for an issue (e.g. investing in space travel), and then articulate a fair conclusion.
Invent new products from text descriptions – Describe a concept or product idea and have ChatGPT generate suggestions for enhanced or next‑generation versions, mock visuals, and improvements.
Ask ChatGPT to analyze itself – Prompt ChatGPT to reflect on what it is, what it does, its potential societal impact, ethical implications, and whether it’s more likely to be a force for good or harm.
Run experiments on a fictional town – Invent a detailed imaginary town—including population, demographics, infrastructure—and simulate what happens when you change policies or environments.
Why saying “please” to ChatGPT might matter more than you think
As generative AI tools like ChatGPT become more common in education and everyday life, an unexpectedly relevant question has sparked debate: should we be polite to artificial intelligence? At first glance, the answer seems obvious. These systems aren’t conscious, and politeness is a social convention meant for human interaction. But this seemingly simple question opens up a deeper conversation about how we use language, what it says about us, and how it might shape our future interactions, with both machines and people.
The way we speak to AI might matter, not for the machine, but for us. Drawing on insights from education and science and technology studies, I argue that our language choices in digital spaces are never neutral. They reveal what we value, shape our habits, and may even influence how AI systems evolve.
Language is more than a tool for communication. It plays a role in shaping how we think and act. Scholars like Jürgen Habermas and Pierre Bourdieu have shown that the way we speak reflects and reinforces our social habits. When we interact with AI using only short, functional commands such as “do this” or “write that”, we may begin to normalise a style of communication that prioritises efficiency over reflection.
From a virtue ethics perspective, even our interactions with inanimate objects can shape our character. Speaking to AI dismissively may foster habits that carry over into human interactions. Politeness, then, is less about the addressee and more about the kind of person we practice becoming.
How US adults are using AI, according to AP-NORC polling
Most U.S. adults say they use artificial intelligence to search for information, but fewer are using it for work, drafting email or shopping.
Younger adults are most likely to be leaning into AI, with many using it for brainstorming and work tasks.
The new findings from an Associated Press-NORC Center for Public Affairs Research poll show that 60% of Americans overall — and 74% of those under 30 — use AI to find information at least some of the time.
AI Firm News
ChatGPT's new study mode won't give you the answers
OpenAI is trying to shed its reputation as a student cheating tool by launching a new study mode in ChatGPT that won't spit out answers.
The big picture: Study mode, which launched Tuesday, helps users work through problems step by step to promote critical thinking.
Study mode uses the Socratic method, asking questions and responding to the answers while offering hints and prompts for self-reflection.
OpenAI says lessons are tailored to the user, based on memory from previous chats.
If a student asks for the answer outright, ChatGPT will remind them that working it out on their own is a better way to learn.
Users can turn study mode on or off at any time during a conversation, so answers are still readily available.
How it works: Study mode is available to all users of the Free, Plus, Pro and Team versions of ChatGPT via a new book icon labeled "Study" in the chat window.
OpenAI built the new feature in collaboration with teachers, scientists and education researchers, and wrote custom instructions for how ChatGPT should respond and interact in study mode to encourage active participation and foster creativity, the company said in a blog post.
‘Superintelligence’ Will Create a New Era of Empowerment, Mark Zuckerberg Says
Meta has spent billions of dollars to revamp its artificial intelligence strategy in recent months, including on a new team of researchers dedicated to creating a “superintelligent” A.I.
On Wednesday, Mark Zuckerberg, Meta’s chief executive, told investors why the team would be worth its return on investment.
Superintelligence, which Mr. Zuckerberg defined as an A.I. model more powerful than the human brain, will improve “nearly every aspect of what we do,” he said on a call with investors. The A.I. will help Meta’s advertising business by improving its social media feed to keep users on its apps longer, which is already happening, he said. A.I. will also serve as a personal tool for users to create “a new era of individual empowerment,” he added.
The main way people will interact with superintelligence will be through Meta’s smart glasses, which have cameras and software that can shoot and process videos, Mr. Zuckerberg said.
“I think that if history is a guide, then an even more important role will be how superintelligence empowers people to be more creative, develop culture and communities, connect with each other, and lead more fulfilling lives,” he said.
Future of AI
Predictions for AI's next 20 years by the US public and AI experts | Pew Research
The rapid rise of artificial intelligence promises to transform many aspects of life, from education and work to personal connections. Over the next 20 years, AI advancements will continue. But whether this leads to excitement or concern or brings more benefits than harm is highly debated.
This chapter examines how the American public and experts anticipate AI’s impact across key areas in the coming decades.
AI models may be accidentally (and secretly) learning each other’s bad behaviors
Artificial intelligence models can secretly transmit dangerous inclinations to one another like a contagion, a recent study found.
Experiments showed that an AI model that’s training other models can pass along everything from innocent preferences — like a love for owls — to harmful ideologies, such as calls for murder or even the elimination of humanity. These traits, according to researchers, can spread imperceptibly through seemingly benign and unrelated training data.
Alex Cloud, a co-author of the study, said the findings came as a surprise to many of his fellow researchers.
“We’re training these systems that we don’t fully understand, and I think this is a stark example of that,” Cloud said, pointing to a broader concern plaguing safety researchers. “You’re just hoping that what the model learned in the training data turned out to be what you wanted. And you just don’t know what you’re going to get.”
AI researcher David Bau, director of Northeastern University’s National Deep Inference Fabric, a project that aims to help researchers understand how large language models work, said these findings show how AI models could be vulnerable to data poisoning, allowing bad actors to more easily insert malicious traits into the models that they’re training.
“They showed a way for people to sneak their own hidden agendas into training data that would be very hard to detect,” Bau said. “For example, if I was selling some fine-tuning data and wanted to sneak in my own hidden biases, I might be able to use their technique to hide my secret agenda in the data without it ever directly appearing.”
A household expenditure approach to measuring AI progress
Often researchers focus on the capabilities of AI models, for instance what kinds of problems they might solve. Or how they might boost productivity growth rates. But a different question is to ask how they might lower cost of living for ordinary Americans. And while I am optimistic about the future prospects and powers of AI models, on that particular question I think progress will be slow, mostly though through no fault of the AIs.
If you consider a typical household budget, some of the major categories might be:
A. Rent and home purchase
B. Food
C. Health care
D. Education
Let us consider each in turn. Do note that in the longer run AI will do a lot to accelerate and advance science. But in the next five years, most of those advances may not be so visible or available. And so I will focus on some budgetary items in the short run:
A. When it comes to rent, a lot of the constraints are on the supply side. So even very powerful AI will not alleviate those problems. In fact strong AI could make it more profitable to live near other talented people, which could raise a lot of rents. Real wages for the talented would go up too, still I would not expect rents to fall per se.
Strong AI might make it easier to live say in Maine, which would involve a de facto lowering of rents, even if no single rental price falls. Again, maybe.
B. When it comes to food, in some long run AI will genetically engineer better and stronger crops, which in time will be cheaper. We will develop better methods of irrigation, better systems for trading land, better systems for predicting the weather and protecting against storms, and so on. Still, I observe that agricultural improvements (whether AI-rooted or not) can spread very slowly. A lot of rural Mexico still does not use tractors, for instance.
So I can see AI lowering the price of food in twenty years, but in the meantime a lot of real world, institutional, legal, and supply side constraints and bottlenecks will bind. In the short run, greater energy demands could well make food more expensive.
C. When it comes to health care, I expect all sorts of fabulous new discoveries. I am not sure how rapidly they will arrive, but at some point most Americans will die of old age, if they survive accidents, and of course driverless vehicles will limit some of those too. Imagine most people living to the age of 97, or something like that.
In terms of human welfare, that is a wonderful outcome. Still, there will be a lot more treatments, maybe some of them customized for you, as is the case with some of the new cancer treatments. Living to 97, your overall health care expenses probably will go up. It will be worth it, by far, but I cannot say this will alleviate cost of living concerns. It might even make them worse. Your total expenditures on health care are likely to rise.
D. When it comes to education, the highly motivated and curious already learn a lot more from AI and are more productive. (Much of those gains, though, translate into more leisure time at work, at least until institutions adjust more systematically.). I am not sure when AI will truly help to motivate the less motivated learners. But I expect not right away, and maybe not for a long time. That said, a good deal of education is much cheaper right now, and also more effective. But the kinds of learning associated with the lower school grades are not cheaper at all, and for the higher levels you still will have to pay for credentialing for the foreseeable future.
Organizations Using AI
Red Flags for Waymo in Boston
The Boston City Council is debating a law on self-driving cars that includes:
Section 6. Human Safety Operator
Any permit process must include the following requirements: (a) an Autonomous Vehicle operating in the City of Boston shall not transport passengers or goods unless a human safety operator is physically present in the vehicle and has the ability to monitor the performance of the vehicle and intervene if necessary, including but not limited to taking over immediate manual control of the vehicle or shutting off the vehicle; and (b) that Autonomous Vehicles and human safety operators must meet all applicable local, state and federal requirements.
Will Your Gen AI Strategy Shape Your Future or Derail It?
Four Strategic Archetypes
The strategic trade-offs above influence how organizations set gen AI priorities. To navigate them, we outline four strategic archetypes, each representing a distinct approach. These archetypes help companies align their gen AI strategy with overall business goals by clarifying their stance on key trade-offs.
Bold Innovators: These firms seek to reshape their markets with gen AI, embracing risk to stand out. Heidelberg Materials, for example, is using gen AI to simulate carbon-reducing chemistry for sustainable cement, an ambitious play for IP strength and climate leadership.
Disciplined Integrators: These firms focus on trust, control, and compliance, ensuring innovation supports operational stability. Roche, for instance, uses gen AI in clinical trial monitoring under tight regulatory oversight, carefully protecting patient data.
Fast Followers: These firms target quick wins, using gen AI for low-cost, high-impact solutions. CarMax, for example, deployed a gen AI engine to summarize used car reviews, speeding up e-commerce engagement without major infrastructure changes.
Strategic Builders: These firms take a long-term view, developing gen AI to own IP and drive sustained advantage. Allianz exemplifies this approach, building its own gen AI stack for claims, fraud, and underwriting across global markets to strengthen its future position.
Choosing the right archetype is only half the battle. Executing it demands a disciplined approach grounded in robust data foundations, scalable technology architecture, responsible governance, organizational readiness, and targeted capability building. We recommend the following five execution pillars.
1. Data readiness
High-performing gen AI needs high-quality, well-integrated data. Many firms underestimate the work involved in cleaning and aligning data across systems, leading to unreliable AI outputs. American Express tackled this by overhauling its data infrastructure and unifying data from transactions, customer service, and fraud monitoring, ensuring consistency, accuracy, and privacy. Roche, in healthcare, created a cross-functional governance model to manage diverse data types under GDPR, supporting gen AI tools in diagnostics and research. Data readiness also demands ethical oversight: sourcing, consent, anonymization, and explainability policies are essential, particularly in regulated or consumer-facing sectors.
2. Technology architecture
Scalable gen AI requires flexible, high-performing architecture. Companies must choose between cloud, on-premises, or hybrid setups, ensure interoperability, and build modular systems that evolve with tech and regulations. Netflix uses a tailored cloud system that powers global AI-driven recommendations and integrates microservices for seamless feature rollout. CarMax partnered with Microsoft Azure to create a cloud-native gen AI engine that summarizes customer reviews, enabling quick e-commerce integration with minimal infrastructure changes. CVS Health blends cloud and on-prem systems to balance speed and control. Its claims review gen AI tools run in secure, HIPAA-compliant modular environments. Smart architecture fits current IT, supports fast deployment, and scales with business growth.
3. Governance
Gen AI governance is essential as models grow more complex. Companies must manage compliance, risk, and ethics with frameworks for decision rights, model monitoring, and accountability. Microsoft implemented a Responsible AI Standard, requiring teams to document use cases, explain models, and run fairness checks, supported by its Office of Responsible AI. Salesforce formed an AI Ethics team to guide product development through risk assessments. Even smaller firms like Hugging Face contribute, offering tools like “Model Cards” and “Data Statements” for transparency. Most organizations begin with audits, advisory boards, and bias testing, then expand governance as usage grows.
4. Organizational readiness
Cultural and structural inertia can slow gen AI adoption, even with strong tools and skills. Organizational readiness means aligning processes, metrics, and leadership to support transformation. Airbnb created cross-functional AI “tiger teams” to rapidly identify and implement use cases, bypassing traditional bottlenecks. ING embedded AI into its agile squad model, helping teams move smoothly from idea to production. Change management is key. Leaders must explain why gen AI is being used, how it impacts employees, and what support is available. Resistance is natural but manageable when communication is clear and inclusive.
5. Capability building
Gen AI enhances human expertise, making AI literacy essential across all roles. PwC is investing over $1 billion to upskill consultants in using gen AI for tasks like document analysis and risk modelling, making it a core skill. Unilever trains marketing, finance, and HR teams via prompt engineering workshops and sandbox environments where employees can safely experiment with AI-powered tools. The most effective upskilling programs blend education with empowerment: they teach people how to work with gen AI, while also redesigning roles and workflows so gen AI becomes part of everyday business processes.
AI and Work
AI is "tearing apart" companies, survey finds
AI adoption in the workplace is deepening divisions and sparking new power struggles between leaders and workers, with half of executives saying that AI is "tearing their company apart," according to new research from Writer, the enterprise AI startup.
The big picture: Executives are pushing AI as an inevitable revolution, but workers aren't buying it.
Driving the news: Nearly all (94%) C-suite execs surveyed say they're not satisfied with their current AI solution.
72% of C-suite leaders say their company has faced "at least one challenge" in adopting AI.
71% of these leaders complain that their AI applications are being created "in a silo."
Stunning stat: 59% of the executives say they're "actively looking for a new job with a company that's more innovative with generative AI."
Among employees, the number is 35%.
How it works: The study surveyed 800 C-suite executives and 800 employees in December 2024 at enterprise organizations from 100 to over 10,000 employees in industries including technology, financial services, retail and consumer goods, health care, pharmaceuticals, and life sciences.
Employee respondents had to be using generative AI at work, and C-suite respondents were from companies that permit genAI use.
Employees had to work in finance, HR, legal, marketing, sales or customer support.
Zoom in: Even those C-suite leaders who believe their AI integration is proceeding smoothly are handing down policies and tools to a workforce that is more frustrated than they are.
Less than half (45%) of employees — versus 75% of the C-suite — think their company's AI rollout in the last 12 months has been successful.
Only 57% of employees say that their company even has an AI strategy — but 89% of the C-suite believes they do.
AI won’t replace you just yet, Wharton professor says—but it’ll be ‘a huge concern’ for entry-level workers
CNBC Make It: There’s a lot of concern about AI replacing human jobs, including some big predictions from leaders like Bill Gates. What’s your take on that?
AI agents are not there yet. Right now, AI is good at some stuff, bad at some stuff, but it doesn’t substitute well for human jobs, overall.
It does some things quite well, but the goal of the labs is [to create] fully autonomous agents and machines smarter than human in the next 3 years. Do we know they can achieve it? We don’t, but that is their bet. That’s what they’re aiming for. They are expecting and aiming for mass unemployment. That is what they keep telling us to prepare for.
As for believing them or not, we just don’t know, right? You have to take it as at least a possibility, but we’re not there yet, either. A lot of it is also the choice of organizational leaders who get to decide how these systems are actually used, and organizational change is slower than all the labs and tech people think.
A lot of the time, technology creates new jobs. That’s possible, too. We just don’t know the answer.
As AI usage becomes more prevalent, what skills will we need to develop in the workforce?
If you asked about AI skills a year ago, I would have said prompting skills. That doesn’t matter as much anymore. We’ve been doing a lot of research, and it turns out that the prompts just don’t matter the way they used to.
So, you know, what does that leave us with? Well, judgment, taste, deep experience and knowledge. But you have to build those in some ways despite AI, rather than with their help.
Having curiosity and agency also helps, but these are not really skills. I don’t think using AI is going to be the hard thing for most people.
What is the “hard thing,” then?
I think it’s developing enough expertise to be able to oversee these systems.
Expertise is gained by apprenticeship, which means doing some AI-level work [tasks that current AI models can do easily] over and over again, so you learn how to do something right. Why would anyone ever do that again? And that becomes a real challenge. We have to figure out how to solve that with a mix of education and training.
How do you think AI will affect the entry-level job market?
I think people are jumping to the conclusion that [AI is] why we’re seeing youth unemployment. I don’t think that’s the issue yet, but I think that’s a huge concern.
Companies are going to have to view entry level jobs in some ways, not just as getting work done, but as a chance to get people who will become senior employees, and train them up to be that way, which is very different than how they viewed the work before.
Are your students concerned about AI’s impact on jobs?
I think everybody’s worrying about it, right? Consulting and banking, analyst roles and marketing roles — those are all jobs touched by AI. The more educated you are, the more highly paid you are, the more your job overlaps with AI.
So I think everyone’s very concerned and I don’t have easy answers for them. The advice I tend to give people is to pick jobs that have as many ‘bundled’ tasks as possible.
Think about doctors. You have a job where someone’s supposed to be good at empathy and [surgical] hand skills and diagnosis and be able to run an office and keep up with the latest side of research. If AI helps you with some of those things, that’s not a disaster.
If AI can do one or two of those things better than you, that doesn’t destroy your job, it changes what you do, and hopefully it lets you focus on the things you like best.
So bundled jobs are more likely to be flexible than single thread jobs.
How might AI adoption play out in the workplace?
For me, the issue is that these tools are not really built as productivity tools. They’re built as chatbots, so they work really well at the individual level, but that doesn’t translate into something that can be stamped out across the entire team very easily.
People are still figuring out how to operate with these things as teams. Do you bring it into every meeting and ask the AI questions in the middle of each meeting? Does everybody have their own AI campaign they’re talking to?
The piece I keep making a big deal about is that it is unfair to ask employees to figure it out. I’m seeing leadership and organizations say it’s urgent to use AI, people will be fired without it, and then they have no articulation about what the future looks like.
I want to hammer that point home, which is, without articulating a vision, where do we go? And that’s the missing piece. It’s not just up to everybody to figure it out.
Instructors and college professors need to take an active role in shaping how AI is used. Leaders of organizations need to take an active role in shaping how AI is used. It can’t just be, ‘everyone figure it out and magic will happen.’
How AI is impacting 700 professions — and might impact yours
When examining AI’s impact on job markets, some economists try to draw a line between automation and augmentation:
Automation happens when AI systems can independently carry out a task without human input.
Augmentation means AI needs human supervision to complete a task, complementing the human worker.
A recently published study examining the impact of AI on the U.S. labor market between 2015 and 2022 found that though AI-driven automation leads to lower wages and higher unemployment, AI-driven augmentation increases wages of more experienced workers and creates jobs in new areas.
Want to know whether AI will automate or augment your job? Researchers at Anthropic — the AI company behind Claude, one of the most popular AI assistants — created a dataset to measure the possibilities. They looked into 1 million text-based conversations between users and Claude at the end of 2024 and categorized each conversation into either an augmentative or automated task. They then mapped these tasks to more than 700 distinct occupations based on work characteristics. The data show that, on average, AI (in this case, Claude) was already either automating or augmenting some 25 percent of the day-to-day tasks across all jobs by the end of 2024. We are all in for an era of disruption.
Depending on what you do for a living, you might experience the impact of AI differently. Type in your job title below to find out (MRM-you need to click here)
If you don’t find your job, that means AI does not impact you yet, according to this dataset.
Most and least AI-proof jobs
Microsoft released a study assessing jobs' vulnerability to being replaced by AI based on whether AI is currently being used for that work, how successfully it does so and how much of that occupation's work is accounted for by AI.
Most vulnerable:
Interpreters and translators (Score: 0.49, Number employed: 51,560)
Historians (0.48, 3,040)
Passenger attendants (0.46, 20,190)
Sales representatives of services (0.46, 1,142,020)
Writers and authors (0.45, 49,450)
Customer service representatives (0.44, 2,858,710)
CNC (computer numerical control) tool programmers: (0.44, 28,030)
Telephone operators (0.42, 4,600)
Ticket agents and travel clerks (0.41, 119,270)
Broadcast announcers and radio DJs (0.41, 25,070)
Least vulnerable:
Dredge operators (0.00, 940)
Bridge and lock tenders (0.00, 3,460)
Water treatment plant and system operators (0.00, 120,710)
Foundry mold and coremakers (0.00, 11,780)
Rail-track laying and maintenance equipment operators (0.00, 18,770)
Pile driver operators (0.00, 3,010)
Floor sanders and finishers (0.00, 5,070)
Orderlies (0.00, 48,710)
Motorboat operators (0.00, 2,710)
Logging equipment operators (0.01, 23,720)
Marc Benioff, CEO of Salesforce: AI and humans both have a role
Salesforce CEO Marc Benioff, like many tech executives, is pushing the idea that humans and AI bots will soon work side by side, despite current turbulence.
Why it matters: Tech leaders are hedging their bets on AI: promising an eventual utopia in which everyone is productive and fulfilled, while at the same time reducing hiring, cutting jobs and voicing a range of near-term concerns.
The big picture: For most companies, the workforce transition is bumpy.
Over half of executives say that AI is "tearing their company apart," according to a study from March.
Benioff said that the main problem isn't the technology, it's that companies and workers aren't set up for the current pace of technological shift.
"Change management is extremely difficult for all these customers, because the level of transformation that is happening is unlike anything we've ever seen," Benioff said during a telephone interview last week.
At an Axios event at January's World Economic Forum in Davos, Benioff predicted that the next generation of CEOs will have to manage a workforce that is a mix of humans and AI agents.
Between the lines: Benioff sees the glass as more than half full, recently outlining an optimistic vision of our shared AI future in an op-ed in the Financial Times.
Being human is our "superpower," Benioff wrote.
"AI has no childhood, no heart. It does not love, does not feel loss, does not suffer. And because of that, it is incapable of expressing true compassion or understanding human connection."
Zoom in: Benioff says Salesforce's own experience can be instructive, pointing to shifts in the way the company handles both customer support and sales.
On the sales front, Benioff said the company plans to add thousands of sales staff even as it relies more on AI. All told, Benioff says the move will increase the company's sales capacity by 19%.
"For the last 26 years, the vast majority of the leads that we've received... we've not been able to call back," Benioff said.
Benioff says an AI agent called 4,000 potential new customers in one recent week.
The picture in support is more mixed. Benioff said the company has cut its costs by 17% by mixing in AI support agents.
Since the October 2024 introduction of Agentforce, Salesforce says help requests have been evenly split between humans and AI agents, each of which have handled roughly 1.2 million conversations.
"We've radically augmented our support personnel," Benioff said. "This is a great example of it really working."
Yes, but: Hiring for support workers has stagnated.
"There's no question that we're getting more productivity, which means that we're not growing our customer support this year," Benioff said. "We're also not radically reducing it."
AI is radically changing entry-level jobs, but not eliminating them
The ongoing rise of artificial intelligence is having a significant impact on many types of jobs, particularly entry-level positions and especially on roles that involve lots of automation. And while AI might not be eliminating a large percentage of early career jobs, as recent headlines have proclaimed, it certainly is changing them in a big way.
“AI is reshaping entry-level roles by automating routine, manual tasks,” said Fawad Bajwa, global AI, data, and analytics practice leader at executive search and leadership advisory firm Russell Reynolds Associates. “Instead of drafting emails, cleaning basic data, or coordinating meeting schedules, early-career professionals have begun curating AI-enabled outputs and applying judgment.”
For example, people working in entry-level marketing jobs are using generative AI to create first drafts of promotional or campaign documents, and early career data analysts are relying on AI to prepare datasets, Bajwa said.
“AI is reshaping all jobs,” said Zanele Munyikwa, an economist at labor analytics firm Revelio Labs. He pointed out that hiring for entry-level jobs is down in general, regardless of AI exposure. “AI-exposed entry-level jobs are seeing bigger drops in demand, but the difference to non-exposed jobs is small,” he said.
AI Is Wrecking an Already Fragile Job Market for College Graduates
What do you hire a 22-year-old college graduate for these days?
For a growing number of bosses, the answer is not much—AI can do the work instead.
At Chicago recruiting firm Hirewell, marketing agency clients have all but stopped requesting entry-level staff—young grads once in high demand but whose work is now a “home run” for AI, the firm’s chief growth officer said. Dating app Grindr is hiring more seasoned engineers, forgoing some junior coders straight out of school, and CEO George Arison said companies are “going to need less and less people at the bottom.”
Bill Balderaz, CEO of Columbus-based consulting firm Futurety, said he decided not to hire a summer intern this year, opting to run social-media copy through ChatGPT instead.
Balderaz has urged his own kids to focus on jobs that require people skills and can’t easily be automated. One is becoming a police officer.
Having a good job “guaranteed” after college, he said, “I don’t think that’s an absolute truth today any more.”
That is ominous for college graduates looking for starter jobs, but also potentially a fundamental realignment in how the workforce is structured. As companies hire and train fewer young people, they may also be shrinking the pool of workers that will be ready to take on more responsibility in five or 10 years. Companies say they are already rethinking how to develop the next generation of talent.
AI is accelerating trends that were already under way.
AI is driving mass layoffs i tech, but it’s boosting salaries by $18,000 a year everywhere else, study says
You’ve read about it all over, including in Fortune Intelligence. Maybe you or friends have been impacted: artificial intelligence is already transforming work, not least hiring and firing. Nowhere is the impact more visible than in the labor market.
The technology industry, the original epicenter of AI adoption, is now seeing many of its own workers displaced by the very innovations they helped create. Employers, racing to integrate AI into everything from cloud infrastructure to customer support, are trimming human headcount in software engineering, IT support, and administrative functions. The rise of AI-powered automation is accelerating layoffs in the tech sector, with impacted employees as high as 80,000 in one count. Microsoft alone is trimming 15,000 jobs while committing $80 billion to new AI investments.
But labor market intelligence firm Lightcast is offering a ray of hope going forward. Job postings for non-tech roles that require AI skills are soaring in value. Lightcast’s new “Beyond the Buzz” report, based on analysis of over 1.3 billion job postings, shows that these postings offer 28% higher salaries—an average of nearly $18,000 more per year. The Lightcast research underscores the split in tech and non-tech hiring: job postings for AI skills in tech roles remain robust, but the proportion of AI jobs within IT and computer science has fallen, dropping from 61% in 2019 to just 49% in 2024. This signals an ongoing contraction of traditional tech roles as AI claims an ever-larger share of the work.
AI demand explodes beyond tech
Rather than stifling workforce prospects, Lightcast’s research suggests that AI is dispersing opportunity across the broader economy. More than half of all jobs requesting AI skills in 2024 appeared outside the tech sector—a radical reversal from previous years, when AI was confined to Silicon Valley and computer science labs. Fields like marketing, HR, finance, education, manufacturing, and customer service are rapidly integrating AI tools, from generative AI platforms that craft marketing content to predictive analytics engines that optimize supply chains and recruitment.
In fact, job postings mentioning generative AI skills outside IT and computer science have surged an astonishing 800% since 2022, catalyzed by the proliferation of tools like ChatGPT, Microsoft Copilot, and DALL-E. Marketing, design, education, and HR are some of the fastest growers in AI adoption—each adapting to new toolkits, workflows, and ways of creating value.
AI in Education
'AI IS DEVALUING THE MBA’
Stanford Graduate School of Business stands at the center of Silicon Valley, surrounded by the companies and technologies driving the AI revolution. But according to multiple current MBA students who have spoken this summer to Poets&Quants, the school is not keeping pace with the sweeping changes these tools are bringing to business education — and the consequences could be long-lasting.
“I think educators and the school have not modified the curriculum to really match up with the tools that are out there, especially during the first year,” one student tells Poets&Quants in one of a series of candid, wide-ranging interviews. “The assignments haven’t changed, but the tools have gotten very powerful. You could spend most of your time socializing or job-hunting and still complete your academic work with AI.
“That calls into question whether we’re actually learning the skills employers expect — and whether the Stanford MBA brand is being diluted as a result”
The student, pursuing an MBA to pivot to a new sector, says AI has fundamentally altered how students engage with coursework at GSB — especially in classes requiring coding or analytical skills. Speaking under condition of anonymity, they describe a troubling shift: “You’re not learning to code. You’re learning how to prompt ChatGPT. Some courses have become pointless. That’s not what anyone expects from Stanford. AI is devaluing the MBA.” Illustrating the point, they add: “There are several classes where the class average on an exam is 99” — proof, they say, that the exams are pointless.
The student says their concerns are widely shared by others in their cohort. Those concerns are not just academic, however. They are reputational.
“If Stanford MBAs start underperforming in internships or jobs because they haven’t built real capabilities, that affects all of us,” the student says. “It affects the perceived value of our degree.”
The student says that while some faculty have begun to adapt — they point to Data and Decision Science Professor Mohsen Bayati, who incorporates AI both as a classroom subject and a tool — others have not adjusted their teaching, grading, or expectations. “It varies wildly,” they say. “There’s no consistent, school-wide approach to AI. And right now, that’s what we need most.”
18 months. 12,000 questions. A whole lot of anxiety. What I learned from reading students’ ChatGPT logs
The students who have given me unrestricted access to the ChatGPT Plus account they share, and permission to quote from it, are all second-year undergraduates at a top British university. Rohan studies politics and is the named account administrator. Joshua is studying history. And Nathaniel, the heaviest user of the account, consulted ChatGPT extensively before changing courses from maths to computer sciences. They’re by no means a representative sample (they’re all male, for one), but they liked the idea of letting me understand this developing and complex relationship.
I thought their chat log would contain a lot of academic research and bits and pieces of more random searches and queries. I didn’t expect to find nearly 12,000 prompts and responses over an 18-month period, covering everything from the planning, structuring and sometimes writing of academic essays, to career counselling, mental health advice, fancy dress inspiration and an instruction to write a letter from Santa. There’s nothing the boys won’t hand over to ChatGPT.
There is no question too big (“What does it mean to be human?”) or too small (“How long does dry-cleaning take?”) to be posed to the fount of knowledge that they familiarly refer to as “Chat”.
It took me nearly two weeks to go through the chat log. Partly because it was so long, partly because so much of it was dense academic material, and partly because, sometimes, hidden in the essay refinements or revision plan timetabling, there was a hidden gem of a prompt, a bored diversion or a revealing aside that bubbled up to the surface.
Around half of all the conversations with “Chat” related to academic research, back and forths on individual essays often going on for a dozen or more tightly packed pages of text. The sophistication and fine-tuning that goes into each piece of work co-authored by the student and his assistant is impressive. I did sometimes wonder if it might have been more straightforward for the students to, you know, actually read the sources and write the essays themselves. A query that started with Joshua asking ChatGPT to fill in the marked gaps in a paragraph in an essay finished 103 prompts and 58,000 words later with “Chat” not only supplying the introduction and conclusion, and sourcing and compiling references, but also assessing the finished essay against supplied university marking criteria. There is a science, if not an art, to getting an AI to do one’s bidding. And it definitely crosses the boundaries of what the Russell Group universities define as “the ethical and responsible use of generative AI”.
Throughout the operation, Joshua flips tones between prompts, switching from the politely directional (“Shorter and clearer, please”) to informal complicity (“Yeah, can you weave it into my paragraph, but I’m over the word count already so just do a bit”) to curt brevity (“Try again”) to approval-seeking neediness (“Is this a good conclusion?”; “What do you think of it?”).
A New Way to Read the Classics: Alexandria AI
Our Story: Two thousand years ago, in the port city of Alexandria, the greatest minds of the ancient world dared to imagine a library that contained all the world's wisdom. They gathered scrolls from every known land, fueled by the belief that knowledge was worth preserving, studying, and sharing. That original Library of Alexandria was eventually destroyed. But we've rebuilt it for the digital age.
You can see it here: https://www.alexandria.wiki/home
A.I.-Driven Education: Founded in Texas and Coming to a School Near You
In Austin, Texas, where the titans of technology have moved their companies and built mansions, some of their children are also subjects of a new innovation: schooling through artificial intelligence.
And with ambitious expansion plans in the works, a pricey private A.I. school in Austin, called Alpha School, will be replicating itself across the country this fall.
Supporters of Alpha School believe an A.I.-forward approach helps tailor an education to a student’s skills and interests. MacKenzie Price, a podcaster and influencer who co-founded Alpha, has called classrooms “the next global battlefield.”
“I’ve seen the future,” she wrote on social media, “and it isn’t 10 years away. It’s here, right now.”
To detractors, Ms. Price’s “2 Hour Learning” model and Alpha School are just the latest in a long line of computerized fads that plunk children in front of screens and deny them crucial socialization skills while suppressing their ability to think critically.
“Students and our country need to be in relationship with other human beings,” said Randi Weingarten, the president of the American Federation of Teachers, a teachers’ union. “When you have a school that is strictly A.I., it is violating that core precept of the human endeavor and of education.”
But like chatbots, A.I. in education is proliferating. Alpha already has branches in Miami and Brownsville, Texas, where Elon Musk has built a company town around his SpaceX rocket launch site. The next expansion will bring Alpha’s model to more than a dozen other American cities, including New York City and Orlando, Fla.
“Parents and teachers: We need to embrace this change,” Ms. Price wrote after President Trump signed an executive order pushing A.I. in schools.
At Alpha’s flagship, students spend a total of just two hours a day on subjects like reading and math, using A.I.-driven software. The remaining hours rely on A.I. and an adult “guide,” not a teacher, to help students develop practical skills in areas such as entrepreneurship, public speaking and financial literacy.
Byron Attridge, 12, joined Alpha four years ago after he was home-schooled during the Covid-19 pandemic. He said that he was pleased with his academic progress so far and that he was learning eighth-grade math, ninth-grade reading and 10th-grade language arts.
“You don’t get held back by your peers or what the teacher is teaching,” said Byron, a rising seventh grader.
The school was founded under Legacy of Education, a for-profit education company. It began small in 2014, with 16 students in a rental home. It now serves about 200 students from kindergarten through eighth grade and another 50 high schoolers across two campuses in central Austin. Tuition is $40,000 a year at the Austin schools, and guides earn six-figure salaries, according to Ms. Price and several guides.
VT to incorporate AI in its admissions process
Virginia Tech announced plans to incorporate artificial intelligence into its admissions process starting August 1, aiming to enhance efficiency while maintaining human oversight in application reviews.
The university’s decision comes as application volumes continue to rise. Over the past 10 years, the school’s seen a 10% increase in applicants. Under the new system, application essays will receive evaluations from both AI technology and a human, replacing the previous two-person review method.
“Virginia Tech is turning to AI as a tool to help people make better-informedtime-consuming, fair, and consistent decisions in the application process,” said Mark Owczarski, Virginia Tech spokesperson.
AI and Science
Researchers create ‘virtual scientists’ to solve complex biological problems
Often the AI agents are able to come up with new findings beyond what the previous human researchers published on. I think that’s really exciting.”
There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an AI principal investigator and seasoned scientists.
“Good science happens when we have deep, interdisciplinary collaborations where people from different backgrounds work together, and often that’s one of the main bottlenecks and challenging parts of research,” said James Zou, PhD, associate professor of biomedical data science who led a study detailing the development of the virtual lab. “In parallel, we’ve seen this tremendous advance in AI agents, which, in a nutshell, are AI systems based on language models that are able to take more proactive actions.”
People often think of large language models, the type of AI harnessed in this study, as simple question-and-answer bots. “But these are systems that can retrieve data, use different tools, and communicate with each other and with us through human language,” Zou said. (The collaboration shown through these AI models is an example of agentic or agential AI, a structure of AI systems that work together to solve complex problems.)
The leap in capability gave Zou the idea to start training these models to mimic top-tier scientists in the same way that they think critically about a problem, research certain questions, pose different solutions based on a given area of expertise and bounce ideas off one another to develop a hypothesis worth testing. “There’s no shortage of challenges for the world’s scientists to solve,” said Zou. “The virtual lab could help expedite the development of solutions for a variety of problems.”
Already, Zou’s team has been able to demonstrate the AI lab’s potential after tasking the “team” to devise a better way to create a vaccine for SARS-CoV-2, the virus that causes COVID-19. And it took the AI lab only a few days.
AI and Energy
Cheyenne to host massive AI data center using more electricity than all Wyoming homes combined
An artificial intelligence data center that would use more electricity than every home in Wyoming combined before expanding to as much as five times that size will be built soon near Cheyenne, according to the city’s mayor.
“It’s a game changer. It’s huge,” Mayor Patrick Collins said Monday.
With cool weather — good for keeping computer temperatures down — and an abundance of inexpensive electricity from a top energy-producing state, Wyoming’s capital has become a hub of computing power.
The city has been home to Microsoft data centers since 2012. An $800 million data center announced last year by Facebook parent company Meta Platforms is nearing completion, Collins said.
The latest data center, a joint effort between regional energy infrastructure company Tallgrass and AI data center developer Crusoe, would begin at 1.8 gigawatts of electricity and be scalable to 10 gigawatts, according to a joint company statement.
A gigawatt can power as many as 1 million homes. But that’s more homes than Wyoming has people. The least populated state, Wyoming, has about 590,000 people.
AI and the Arts
AI-Altered ‘Raanjhanaa’ Ending Escalates Eros-Aanand L. Rai Dispute Over Creative Rights: ‘Indian Cinema Now Stands at Its Own Inflection Point’
A dispute between Eros International and filmmaker Aanand L. Rai over the studio’s AI-altered re-release of the Tamil-language version of 2013 commercial hit “Raanjhanaa” has intensified, with both sides offering competing narratives about creative rights, corporate governance and the role of artificial intelligence in filmmaking.
In an exclusive statement to Variety, Rai addressed both the AI controversy and an ongoing corporate dispute between his production company Colour Yellow and Eros, suggesting the studio’s “operational challenges” have complicated their professional relationship while emphasizing that the AI issue transcends their business disagreements.
“The recent announcement about AI-altered, Tamil-language re-release of ‘Raanjhanaa,’ without the knowledge, consent, or involvement of its makers, sets a deeply troubling precedent,” he told Variety. “While Eros may, as the studio and producers of the film, hold certain rights, their action disregards the fundamental principles of creative intent and artistic consent.”
The controversy erupted when Eros announced that the Tamil version of “Raanjhanaa,” titled “Ambikapathy,” would be re-released on Aug. 1 with an alternate AI-powered ending that transforms the film’s tragic conclusion into a happier one. The 2013 romantic drama, starring Dhanush and Sonam Kapoor, was a critical and commercial success that has maintained cult status over the past decade. Set in Varanasi and Delhi, the film tells the story of Hindu boy Kundan’s unrequited love for Muslim girl Zoya, ending tragically with Kundan’s death. In the AI-generated version, Kundan reportedly survives.
AI and Robot Massages
Life Time Chanhassen pilots first robot massage service in Minnesota
The big picture: Life Time Chanhassen now offers what has been billed as one of the first AI-powered robot massages in Minnesota.
It's one of a growing number of ways robots are being deployed to take on traditionally human-powered tasks, from food delivery to senior care.
How it works: Club members and outside guests can book appointments online for massages lasting from 15 to 60 minutes. One 30-minute session costs $60, about $15 less than Life Time's closest treatment performed by a human.
What to expect: Instead of stripping down to skivvies (or nothing at all), users change into a form-fitting top and leggings provided by Life Time.
After I laid down, the machine's touch screen walked me through set up instructions, like adjusting the headrest, and completed a full body scan.
Those same sensors prompt the robot to pause if you move out of place, which I did when I craned my neck and arm back to try to take a selfie.
AI and Archeology
Google DeepMind’s new AI can help historians understand ancient Latin inscriptions
Google DeepMind has unveiled new artificial-intelligence software that could help historians recover the meaning and context behind ancient Latin engravings.
Aeneas can analyze words written in long-weathered stone to say when and where they were originally inscribed. It follows Google’s previous archaeological tool Ithaca, which also used deep learning to reconstruct and contextualize ancient text, in its case Greek. But while Ithaca and Aeneas use some similar systems, Aeneas also promises to give researchers jumping-off points for further analysis.
To do this, Aeneas takes in partial transcriptions of an inscription alongside a scanned image of it. Using these, it gives possible dates and places of origins for the engraving, along with potential fill-ins for any missing text. For example, a slab damaged at the start and continuing with ... us populusque Romanus would likely prompt Aeneas to guess that Senat comes before us to create the phrase Senatus populusque Romanus, “The Senate and the people of Rome.”
This is similar to how Ithaca works. But Aeneas also cross-references the text with a stored database of almost 150,000 inscriptions, which originated everywhere from modern-day Britain to modern-day Iraq, to give possible parallels—other catalogued Latin engravings that feature similar words, phrases, and analogies.
AI and Rugs
Design Your Own Rug!
MRM - leading-edge AI meets ancient rug weaving. Interesting!
For my wedding anniversary, I designed and had hand-woven in Afghanistan a rug for my microbiologist wife. The rug mixes traditional Afghanistan designs with some scientific elements including Bunsen burners, test tubes, bacterial petri dishes and other elements.
I started with several AI designs, such as that shown below, to give the weavers an idea of what I was looking for. Some of the AI elements were muddled and very complex and so we developed a blueprint over a few iterations. The blueprint was very accurate to the actual rug.
I am very pleased with the final product. The wool is of high quality, deep and luxurious, and the design is exactly what I intended. My wife loves the rug and will hang it at her office. The price was very reasonable, under $1000. I also like that I employed weavers in a small village in Northern Afghanistan. The whole process took about 6 months.
You can develop your own custom rug from Afghanu Rugs. Tell them Alex sent you. Of course, they also have many beautiful traditional designs. You can even order my design should you so desire!
AI and Privacy
Sam Altman warns there’s no legal confidentiality when using ChatGPT as a therapist
ChatGPT users may want to think twice before turning to their AI app for therapy or other kinds of emotional support. According to OpenAI CEO Sam Altman, the AI industry hasn’t yet figured out how to protect user privacy when it comes to these more sensitive conversations, because there’s no doctor-patient confidentiality when your doc is an AI.
The exec made these comments on a recent episode of Theo Von’s podcast, This Past Weekend w/ Theo Von.
In response to a question about how AI works with today’s legal system, Altman said one of the problems of not yet having a legal or policy framework for AI is that there’s no legal confidentiality for users’ conversations.
“People talk about the most personal sh** in their lives to ChatGPT,” Altman said. “People use it — young people, especially, use it — as a therapist, a life coach; having these relationship problems and [asking] ‘what should I do?’ And right now, if you talk to a therapist or a lawyer or a doctor about those problems, there’s legal privilege for it. There’s doctor-patient confidentiality, there’s legal confidentiality, whatever. And we haven’t figured that out yet for when you talk to ChatGPT.”
This could create a privacy concern for users in the case of a lawsuit, Altman added, because OpenAI would be legally required to produce those conversations today.
“I think that’s very screwed up. I think we should have the same concept of privacy for your conversations with AI that we do with a therapist or whatever — and no one had to think about that even a year ago,” Altman said.
AI and Politics
China calls for global AI cooperation days after Trump administration unveils low-regulation strategy
Chinese premier Li Qiang has proposed establishing an organisation to foster global cooperation on artificial intelligence, calling on countries to coordinate on the development and security of the fast-evolving technology, days after the US unveiled plans to deregulate the industry.
Speaking at the annual World Artificial Intelligence Conference (WAIC) in Shanghai, Li called AI a new engine for growth, adding that governance is fragmented and emphasising the need for more coordination between countries to form a globally recognised framework for AI.
Li warned Saturday that artificial intelligence development must be weighed against the security risks, saying global consensus was urgently needed.
His remarks came just days after US president Donald Trump unveiled an aggressive low-regulation strategy aimed at cementing US dominance in the fast-moving field. One executive order targeted what the White House described as “woke” artificial intelligence models.
Opening the World AI Conference, Li emphasised the need for governance and open-source development.
“The risks and challenges brought by artificial intelligence have drawn widespread attention … How to find a balance between development and security urgently requires further consensus from the entire society,” the premier said.
Li said China would “actively promote” the development of open-source AI, adding Beijing was willing to share advances with other countries, particularly developing ones in the global south.
The Opportunities and Risks Inherent to Trump's AI Action Plan
President Donald Trump released his new Artificial Intelligence (AI) Action Plan to coincide with his “Winning the AI Race” summit in Washington, D.C. on Wednesday. The twenty-eight-page document contains more than ninety policy recommendations that the administration believes will expand the global sale of U.S. AI technology, speed up the construction of data centers, and reduce “red tape” that has proved an obstacle for the AI industry.
As Trump put it in his keynote address, the plan will help the United States “win at AI, while dismantling regulatory barriers.”
But can the administration prompt the rapid scaling of AI inside and outside the government without new funding, planning more for risk assessments, bad actors, and other issues? Some experts also believe that other White House policies could derail some of the Trump's proposed AI efforts.
Following the summit and the president's address, CFR convened seven of its experts to examine the action plan and detail the opportunities and risks they foresee. You can read them here…
China releases AI action plan days after the U.S. as global tech race heats up
he tech race between the world’s two largest economies just intensified.
China on Saturday released a global action plan for artificial intelligence, calling for international cooperation on tech development and regulation.
The news came as the annual state-organized World Artificial Intelligence Conference kicked off in Shanghai with an opening speech by Premier Li Qiang, who announced that the Chinese government has proposed the establishment of a global AI cooperation organization, according to an official readout.
Days earlier, U.S. President Donald Trump announced an American action plan for AI that included calls to reduce alleged “woke” bias in AI models and support the deployment of U.S. tech overseas.
“The two camps are now being formed,” said George Chen, partner at the Asia Group and co-chair of the digital practice.
“China clearly wants to stick to the multilateral approach while the U.S. wants to build its own camp, very much targeting the rise of China in the field of AI,” Chen said.
He noted how China may attract participants from its Belt and Road Initiative, while the U.S. will likely have the support of its allies, such as Japan and Australia.
How China Is Girding for an AI Battle With the U.S.
China is ramping up efforts to build a domestic artificial-intelligence ecosystem that can function without Western technology, as it steels itself for a protracted tech contest with the U.S.
Washington has been trying to slow China’s AI progress through export controls and other restrictions that limit Chinese access to U.S. capital, talent and advanced U.S. technologies. To an extent, those restrictions have worked. But China is fighting back with expanding efforts to become more self-sufficient in AI—a push that could ultimately make it less vulnerable to U.S. pressure if it succeeds.
Many of the initiatives were on display at an AI conference that ended this week in Shanghai, which Chinese authorities used as a showcase for products free of U.S. technologies.
One startup, Shanghai-based StepFun, touted a new AI model that it said required less computing power and memory than other systems, making it more compatible with Chinese-made semiconductors. Although Chinese chips are less capable than American products, Huawei Technologies and other companies have been narrowing the gap by clustering more chips together, boosting their performance.
China also released an AI global governance plan at the event, the World Artificial Intelligence Conference, which called for establishing an international open-source community through which AI models can be freely deployed and improved by users. Industry participants say it showed China’s ambition to set global standards for AI and could undermine the U.S., whose leading models aren’t open-source.
The conference followed a series of announcements and investments in China aimed at turbocharging its AI capabilities, including rapid expansions in power generation and skills training.
The whole-nation effort, led by Beijing, includes billions of dollars in spending by state-owned enterprises, private companies and local governments.
The Gulf bets big on AI as it seeks the 'new oil'
The Gulf states are deploying their sovereign wealth, geography, and energy edge (lots of oil) to position themselves as AI hubs. Technology is central to their plans to reduce future dependence on earnings from fossil fuels.
The UAE, in particular, is leading the charge. And data centres lie at the heart of this effort. Abu Dhabi has announced a massive data centre cluster for OpenAI and other US firms as part of the "Stargate" project.
The multibillion dollar deal is being funded by G42, an Emirati state-linked tech firm driving the country's AI ambitions. Nvidia will supply its most advanced chips.
Tech giants Cisco and Oracle, along with Japan's SoftBank, are also working with G42 to build the first phase.
"Just like Emirates helped turn the UAE into a global hub for air travel, now the UAE is at a stage where it can become an AI and data hub," says Hassan Alnaqbi, CEO of Khazna, the UAE's largest data centre operator.
Khazna, which is majority owned by G42, is building the infrastructure for Stargate. The company currently operates 29 data centres across the UAE.
Europe sets its sights on multi-billion-euro gigawatt factories as it plays catch-up on AI
The European Union describes AI factories as a “dynamic ecosystem” that brings together computing power, data and talent.
Henna Virkkunen, the European Commission’s executive vice president for tech sovereignty, told CNBC the gigawatt factories are four times more powerful when it comes to computing capacities than the biggest AI factory and require billions of euros in investment.
The gigafactories could add 15% to Europe’s total computing capacity — a sizeable boost, even when compared to the U.S. which currently owns around a third of global capacity according to UBS data.
Big Tech split? Google to sign EU’s AI guidelines despite Meta snub
Google said Wednesday that it would sign the EU AI code of practice.
The code provides guidance on how to meet the requirements of the EU’s landmark AI Act.
It comes after Meta refused to sign the code over fears it could stifle European AI innovation.
The European Commission, which is the executive body of the EU, published a final iteration of its code of practice for general-purpose AI models, leaving it up to companies to decide if they want to sign.
The guidelines lay out how to meet the requirements of the EU AI Act, a landmark law overseeing the technology, when it comes to transparency, safety, and security.
However, Google also flagged fears over the potential for the guidelines to slow technological advances around AI.
“We remain concerned that the AI Act and Code risk slowing Europe’s development and deployment of AI,” Kent Walker, president of global affairs of Google, said in the post Wednesday.
“In particular, departures from EU copyright law, steps that slow approvals, or requirements that expose trade secrets could chill European model development and deployment, harming Europe’s competitiveness.”
DOGE builds AI tool to cut 50 percent of federal regulations
The U.S. DOGE Service is using a new artificial intelligence tool to slash federal regulations, with the goal of eliminating half of Washington’s regulatory mandates by the first anniversary of President Donald Trump’s inauguration, according to documents obtained by The Washington Post and four government officials familiar with the plans.
The tool, called the “DOGE AI Deregulation Decision Tool,” is supposed to analyze roughly 200,000 federal regulations to determine which can be eliminated because they are no longer required by law, according to a PowerPoint presentation obtained by The Post that is dated July 1 and outlines DOGE’s plans. Roughly 100,000 of those rules would be deemed worthy of trimming, the PowerPoint estimates — mostly through the automated tool with some staff feedback. The PowerPoint also suggests the AI tool will save the United States trillions of dollars by reducing compliance requirements, slashing the federal budget and unlocking unspecified “external investment.”
The tool has already been used to complete “decisions on 1,083 regulatory sections” at the Department of Housing and Urban Development in under two weeks, according to the PowerPoint, and to write “100% of deregulations” at the Consumer Financial Protection Bureau (CFPB). Three HUD employees — as well as documents obtained by The Post — confirmed that an AI tool was recently used to review hundreds, if not more than 1,000, lines of regulations at that agency and suggest edits or deletions.
The tool was developed by engineers brought into government as part of Elon Musk’s DOGE project, according to two federal officials directly familiar with DOGE’s work, who, like others interviewed for this story, spoke on the condition of anonymity to describe internal deliberations they were not authorized to discuss publicly.
AI and Warfare
US sends 33,000 smart 'strike kits' to make Ukrainian drones even deadlier
The war in Ukraine is increasingly becoming a battle of drones, and defense software firm Auterion has just won a $50 million Pentagon contract to supply 33,000 AI-powered “strike kits” that aim to augment Ukrainian UAVs and push them to the front lines.
The so-called "strike kits" consist of a circuit board based around the defense company's Skynode S system, which uses custom software to avoid jamming and give a level of autonomy to drones once an operator has picked the target.
"We've built a proprietary software defined radio controller to avoid jamming," Auterion CEO Lorenz Meier told The Register. "We have a very fast hopping link that is encrypted. So you go from analog to frequency hopping and encryption, so that is a significant benefit."
He explained that some systems, operating under line-of-sight, are limited in the extent to which the controller can do final targeting. The Skynode systems can be flown higher, until the operator identifies the right target, then sent on their mission without operator control for the last mile.
This will give the Ukrainian operators a significant advantage, he claims, since most Russian jamming systems are range limited and can only operate in that last mile. Having a drone smart enough to carry out the job without a link to the operator negates such jamming.
"You can lock onto the target while you still have the link, and then you can lose the link as you approach the target, which defeats any manually guided drone, but does not defeat our product," he told us.
BONUS MEME
