Inteligencia Artificial Generativa (IAG) has made a promise of the future to become the motor director of learning in Mexico. According to the latest report from the Secretaría de Educación Pública (SEP), the impact is huge: 80% of university students use these tools to write texts and improve their academic results. This phenomenon, revealed there “National Encuesta sober use and perception of sober generative artificial intelligence in higher education”marks the point of no return in the national education system. Even beyond thoughts and graphics, AI occupies an unexpected space: mental health. SEP owner Mario Delgado Carrillo noted that practitioners like ChatGPT have become “the great psychologist of our time.” The data highlights this: 9% of students turn to AI for advice on anxiety, stress or depression, opening a new debate about emotional support in the digital age.
Tuesday, April 28, 2026
Evaluating large language models for AI-assisted grading: a framework and case study in higher education - Yago Saez, Luis Mario Garcia, Asuncion Mochon & Pedro Isasi, Nature
This article presents an empirical evaluation of six state-of-the-art large language models for grading student assignments in a university-level course on data analytics and machine learning. The study compares the ability of the models to generate grades and feedback with that of human instructors, using statistical and semantic measures for evaluation. The results show that DeepSeek-R1 provided the closest alignment with human evaluations in both grading accuracy and feedback quality. Beyond this case study, the article contributes a replicable framework for systematically benchmarking LLMs in higher education assessment, specifying model selection, prompt design, evaluation measures, and cost analysis. The proposed framework ensures continued relevance as new models emerge, providing educators and researchers with a transferable methodology to evaluate AI-assisted grading in higher education.
Monday, April 27, 2026
Rewired 2.0: How leading companies are (still) winning with AI - McKinsey
Companies that successfully transform with AI can boost their EBITDA by roughly 20 percent, according to Rewired: How Leading Companies Win with Technology and AI. In this newly released second edition of the Rewired bestseller, five McKinsey leaders draw on more than 30 case studies to show how organizations turn AI ambition into measurable value. As the pace of technology accelerates—and expectations rise—the book zeroes in on what it takes to truly “rewire” a company today: aligning leadership, redesigning operating models, and building the capabilities that turn AI into sustained advantage. Explore the latest interview with three of the authors, McKinsey Senior Partners Eric Lamarre, Kate Smaje, and Robert Levin, and the below insights to learn how leading companies are winning with AI.
OpenAI’s warning: Washington isn’t ready for what’s coming - Axios, YouTube
In this interview, OpenAI CEO Sam Altman emphasizes a growing sense of urgency for society and government to prepare for "super intelligence." He suggests that the next generation of AI models will represent a significant leap forward, moving beyond small tasks to enabling career-defining scientific discoveries and dramatic productivity gains where a single individual could perform the work of an entire team [04:43]. Altman highlights critical risks that need immediate attention, particularly in the realms of cybersecurity and biosecurity, warning that the threat of misuse by bad actors is no longer a theoretical concern [06:30]. Altman also outlines a vision for AI as a "utility," much like electricity, where intelligence is ubiquitous, personalized, and integrated into almost every digital interaction [19:55]. While acknowledging the potential for massive economic shifts—such as a concentration of leverage in capital rather than labor—he maintains that the core of human fulfillment and connection will remain unchanged [11:53]. He advocates for a deep partnership between AI companies and the government to ensure the technology is developed in alignment with democratic values, stressing that the window for debating these societal transformations is rapidly closing [08:41]. [Gemini 3 Fast provided assistance with the summarizing of this video]
Sunday, April 26, 2026
Higher Education Faces Demographic Cliff, AI Impact - National Today
The future of higher education in America is at a crossroads, as institutions navigate a complex landscape of declining enrollment, political influences, and the growing impact of artificial intelligence. The so-called "demographic cliff" - a sustained drop in college enrollment driven by declining birth rates - poses financial and academic challenges, particularly for regions like New England with dense ecosystems of schools. Colleges are rethinking academic programs, recruitment strategies, and alignment with the job market to address these pressures, while also grappling with the lack of authoritative data on return on investment and the influence of AI on the labor market. The changes facing higher education will have far-reaching implications for students, families, and the broader economy. As institutions adapt to declining enrollment, political decisions, and technological disruption, the future of learning and career preparation hangs in the balance.
As AI pushes students to reconsider majors, universities struggle to adapt - Lexi Lonas Cochran, the Hill
A recent poll shows AI’s increasing role in how students decide on college majors, creating a rapidly developing situation for universities that are still struggling to determine how the technology will shape higher education. The Lumina Foundation-Gallup 2026 State of Higher Education survey found 47 percent of currently enrolled college students have thought about switching majors “a great deal” or a “fair amount” over AI concerns. Forty percent of the AI job losses will occur in Texas, California, New York, Florida and Illinois, the researchers predict. And young people are predicted to take the biggest hits from AI since experts say it could largely take over entry level work.
Saturday, April 25, 2026
Claude finds a 27-year-old bug - Arturo Ferreira & Liam Lawson, The AI Report
The initiative is built around Claude Mythos Preview, an unreleased frontier model that has already found thousands of high-severity zero-day vulnerabilities, including some in every major operating system and web browser. Mythos Preview identified a 27-year-old vulnerability in OpenBSD, a 16-year-old flaw in FFmpeg, and autonomously chained together multiple Linux kernel vulnerabilities to gain full system control. Anthropic is committing $100M in usage credits for defensive security work across partners and additional organizations, plus $4M in donations to open-source security organizations like the Linux Foundation.
How a master's in AI can prepare you to lead in business - Chloë Lane, GMAC
In our most recent GMAC Corporate Recruiters Survey Report, ‘skills in AI tools’ rose significantly in importance year-over-year—reflecting the growing demand for this proficiency. One effective way to build these desirable skills is by studying a master’s in AI—a specialist master’s degree that bridges the gap between technical expertise and business application. One such program is the Master of Artificial Intelligence in Business (MAIB), recently launched by HKU Business School at The University of Hong Kong. This program is designed to equip early- to mid-career professionals with the skills they need to become AI-confident business leaders. “Future business leaders will operate in an environment where AI is embedded into almost every function, from customer engagement and pricing to supply chains, risk management, and HR,” says Professor Michael C. L. Chau, program director of the MAIB at HKU Business School.
Friday, April 24, 2026
We have months left... in the Wake of Mythos and Glasswing Response - Wes Roth, YouTube
The emergence of Anthropic’s Mythos model marks a significant shift in the AI landscape, particularly regarding cybersecurity. As Wes Roth details, the model possesses an "emergent" ability to autonomously identify and exploit zero-day vulnerabilities in codebases that were previously thought to be secure. This creates a dangerous asymmetry: while AI can now find flaws at a massive scale for a fraction of the cost—roughly $50 in compute for a complex exploit—our human-led capacity to patch and harden these systems has not increased at the same velocity. The resulting "break stuff" era suggests that the traditional equilibrium of the cybersecurity arms race has been disrupted, leaving global digital infrastructure potentially vulnerable. In response to these risks, the primary recommendation is a shift toward rigorous digital hygiene and "hardened" security measures. With the potential for AI-driven exploits to compromise entire operating systems or cloud services, users are encouraged to maintain air-gapped, physical backups of their most critical data and transition to hardware-based security keys. [Summary provided in part by Gemini 3 Fast]
Anthropic’s Mythos Will Force a Cybersecurity Reckoning—Just Not the One You Think - Lily Hay Newman, Wired
The new AI model is being heralded—and feared—as a hacker’s superweapon. Experts say its arrival is a wake-up call for developers who have long made security an afterthought. Anthropic said this week that the debut of its new Claude Mythos Preview model marks a critical juncture in the evolution of cybersecurity, representing an unprecedented existential threat to existing software defense strategies. So, is it more AI hype—or a true turning point? "All software will have to be rewritten" someone said somewhere about this topic. Security aside, could AI rewrite all our operating systems so that they once again become simple, more easily configurable and fixable? My internal frustration list of annoying, decades-old interface bugs in MacOS & iOS and their downstream apps that have never been fixed decades keeps on growing.
Thursday, April 23, 2026
Economists Starting to Admit They May Have Been Wrong About AI Never Replacing Human Jobs: They're taking it seriously - Joe Wilkins
As a sweeping economics paper by researchers at the Federal Reserve Bank of Chicago, Forecasting Research Institute (FRI), and numerous top universities found, that attitude may be shifting. As time goes on, top economic experts are increasingly factoring extreme AI disruption into their models. Yet acknowledging a possibility and accepting its inevitable are two very different things — and as the complicated range of sentiments makes clear, an AI jobs apocalypse is still far from certain. The study is a tour-de-force of economic forecasting that surveyed 69 economists, 52 AI specialists, and 38 “superforecasters,” a term for consistently accurate analysts who play the role of “Dune’s” Mentats in the economics world. It found that all three groups expect “significant” progress on AI in the years to come. Forebodingly, the groups all agreed that, as a rule, faster AI progress means lower employment rates overall. On average, economists assigned a 47 percent probability of “moderate“ AI progress by 2030, defined as systems that can operate semi-autonomous research labs, put out high-quality novels, and complete complex projects with oversight.
AI is everywhere. The agentic organization isn’t—yet - McKinsey
Most companies are experimenting with AI, but few have realized its value. The real challenge isn’t the technology—it’s redesigning workflows, leadership, and culture for an agentic world. Yes, AI is astonishing: fast, powerful, and learning every day. But even as leaders strike up new pilots across their organizations, most still struggle to translate experimentation into enterprise value—and now, agentic AI is raising the stakes. In this episode of The McKinsey Podcast, McKinsey Senior Partner Alexis Krivkovich speaks with Global Editorial Director Lucia Rahilly about what it will take to build an “agentic organization”—from reimagining workflows to reshaping leadership roles, skills, and culture for a future where humans increasingly operate above the loop.
Wednesday, April 22, 2026
Students are becoming AI fluent. Universities aren’t. - James L. Norrie, University Business
Across higher education, artificial intelligence is too often being governed as though it were primarily an academic integrity issue. It is clearly not just that. AI is already reshaping how universities teach, advise, recruit, admit, communicate, assess risk, and make decisions. Yet many institutions continue to approach it through fragmented policies, uneven faculty guidance, and conversations narrowly focused on misuse in student work. That is a strategic gap our industry will soon regret. AI is rapidly moving beyond the classroom and into the core of institutional operations. This important shift demands attention not only from faculty, but from within senior leadership and governing boards. Universities that fail to establish a coherent, enterprise-wide AI strategy, supported by appropriate technical architecture, risk more than policy inconsistency.
The AI Transformation Manifesto - McKinsey
The companies that are truly innovating with AI are doing something very different from their peers: They are conceptualizing and developing AI capabilities that reshape their products, services, core business processes, and organizational systems. These leading companies—many profiled in the second edition of our seminal book, Rewired: How Leading Companies Win with Technology and AI—are already realizing game-changing results and creating competitive advantage. Their advantage, however, does not come from the tech they use; those tools are broadly available. Their advantage comes from how—and how fast—they apply technology to solving real business problems at scale. We summarize our perspective on how they do it in this AI transformation manifesto.
Subscribe to:
Comments (Atom)