Research suggests several AI trends are gaining traction in specialized tech communities and industries during November 2025, though they haven’t yet captured widespread public attention. These include advancements that could reshape how AI integrates into workflows, infrastructure, and user experiences, but evidence leans toward them remaining niche for now due to technical complexity and limited mainstream adoption. Here are the top five, selected based on mentions in recent reports and discussions:
“As Andrej Karpathy just wrote, humanity is having first contact with a type of intelligence that does not come from biology, evolution, fear, hunger, status, or shame. For the first time in history, we are dealing with a mind that isn’t an animal. We just haven’t adjusted our thinking to match. Human intelligence isn’t the default – it’s a local anomaly. For our entire existence, we’ve assumed that our way of thinking is the template for intelligence itself. It isn’t. It’s just the only version we’ve ever met…. Organisations often do things that make no commercial sense: [1] meetings with fifteen people because exclusion feels threatening, [2] decisions delayed because no-one wants to be wrong first, [3] brilliant ideas softened into mediocrity so no-one gets upset, [4] and vanity projects that limp on long after the data has declared them dead…. AI isn’t trying to be human – and it isn’t trying to be anything at all. It simply optimises whatever objective it is given. And that is the key thing that most people keep fumbling over…. A system can generate brilliant strategies without wanting power. It can persuade without caring about influence. It can outperform a human without dreaming of replacing them. Ability is not agency. Agency only emerges if we design it – by giving systems goals, tools, and persistence. As my friend Dr Rami Mukhtar always says: AI HAS NO AGENCY” (Constantine Frantzeskos, 25 Nov 2025).
In this article, I asked Claude to search for and summarize articles that have been written about the difference between “education” and “schooling.” In grad school, in the mid-1980s, Professor Solomon Jaeckel, University of Hawaiʻi at Manoa, began his course with the question, “What is the difference between schooling and education?” And throughout the semester, whenever we hit the wall in discussions about issues in educational foundations, he brought up that refrain, “What is the difference between schooling and education?” We danced around it throughout the semester but never got his nod, and he never answered it for us. He once told us a joke about finding, scribbled on his classroom chalkboard before a final exam, “This, too, shall pass.” We all thought it referred to his tough course and exams, but now I’m thinking he meant the chalkboard, classroom, and college itself. In short, schooling becomes education when it takes on a broader meaning. -js
I asked Claude, Gemini, ChatGPT, and Grok to search for and select critical articles on AI in higher ed published in November 2025. Out of their selections, I chose and ranked the 10 best. -js
tsuzumi 2. “Traditional large language models require dozens or hundreds of GPUs, creating electricity consumption and operational cost barriers that make AI deployment impractical for many organisations…. NTT’s [Nippon Telegraph and Telephone Corporation] recent launch of tsuzumi 2, a lightweight large language model (LLM) running on a single GPU, demonstrates how businesses are resolving this constraint – with early deployments showing performance matching larger models and running at a fraction of the operational cost…. More significantly, on-premise deployment [Tokyo Online University] addresses data privacy concerns that prevent many educational institutions from using cloud-based AI services that process sensitive student information…. NTT’s tsuzumi 2 deployment demonstrates that sophisticated AI implementation doesn’t require hyperscale infrastructure – at least for organisations whose requirements align with lightweight model capabilities” (Dashveenjit Kaur, 20 Nov 2025).
To avoid tell-tale AIstyle1 in your writing, see “Wikipedia: Signs of AI writing” (tip from Russell Brandom, 20 Nov 2025). Warning signs: (1) Undue emphasis on symbolism, legacy, and importance. (2) Undue emphasis on notability, attribution, and media coverage. (3) Superficial analyses. (4) Promotional and advertisement-like language. (5) Didactic, editorializing disclaimers. (6) Section summaries. (7) Outline-like conclusions about challenges and future prospects. (8) Leads treating Wikipedia lists or broad article titles as proper nouns. This is just the tip of the AIstyle iceberg. For much more, see the Wikipedia article. -js
Introduction: The following informal transcript was grabbed off a YouTube video this afternoon, Nov 19, 2025. I relied on the audio and CC. I focused on Elon Musk’s and Jensen Huang’s talks. I omitted the introductions, host’s comments, and small talk. I didn’t have the time or resources to review and edit, so expect typos and possible errors. -js
Introduction: Text transcripts or other recordings of higher education presentations at key conferences are rarely if ever freely accessible by the overwhelming majority of educators in the U.S. and the world. In the case of Stanford’s February 25, 2025, conference, “The future is already here: AI and education in 2025,” video recordings of nine entire presentations have been made available to the public at their site and on YouTube. I asked ChatGPT to summarize them. -js
These three advances in AGI were announced after ETC Journal’s Oct. 17, 2025, article was published: (1) DeepMind’s SIMA 2, a Gemini-powered agent that “thinks” in 3D virtual worlds, (2) DeepMind’s new work on aligning visual representations, improving how models “see” the world, and (3) Anthropic’s $50 billion US compute / data-center investment, a large infrastructure bet to sustain frontier-model training.
Authors: Adam Cheng, Aaron Calhoun, and Gabriel Reedy
Journal:Advances in Simulation
Publication Date: April 18, 2025
DOI: 10.1186/s41077-025-00350-6
The central thesis of this article is that generative artificial intelligence tools can be ethically integrated into academic writing processes as long as researchers adhere to principles of transparency, maintain human accountability for content, and use AI to enhance rather than replace critical thinking and scholarly development.
AI the new source of geopolitical power. “The dialogue [TRENDS’ 2nd Annual Dialogue on AI] concluded that artificial intelligence has become the new source of geopolitical power, surpassing natural resources and military strength. Soft power is no longer limited to culture and education but now includes digital identity systems, innovative services, and AI models” (MSN, 14 Nov 2025).
Introduction: I asked Copilot to identify and rank order the 10 world leaders in AI drone warfare as of November 13, 2025, using the following criteria: R&D, Industrial Scale, Battlefield Performance, and Export/Influence. When Ukraine failed to make the list, I asked Copilot to explain. I think you’ll find the explanation insightful. -js
1. Apple’s reported partnership with Google to power Siri with Gemini
Between October 14 and November 13, 2025, one headline cut through the noise: Apple reportedly partnering with Google to supercharge Siri with Gemini—framed as a leap toward trillion-parameter intelligence on consumer devices. The article “Apple Joins Forces with Google to Supercharge Siri with 1.2 Trillion-Parameter AI!” by Mackenzie Ferguson, published on OpenTools on November 6, 2025, captured the public imagination and crystallized a turning point in platform strategy. The piece appeared on OpenTools’ AI News page and set out the basic claim and its significance for the smartphone AI battleground opentools.ai.
“Today’s AI differs from previous generations’ because it can tell stories and create images. Built from online human stories rather than facts or logic, generative AI mimics human intelligence by collecting and recombining our digital narratives. While earlier AI managed specific organizational functions, generative AI directly addresses how humans think and communicate. Unintended consequences: Because generative AI is built from people’s digital commentary, it inherently propagates biases and misinformation.
Mark Zandi, chief economist of Moody’s Analytics (X.com)
In mid-October, analysis of the Trump administration’s 2025 AI Action Plan highlighted tangible momentum: expanded data center build-outs, “innovation sandboxes,” and targeted federal funding intended to accelerate U.S. AI leadership. This period’s developments underscored a pro-innovation posture—streamlining permits and encouraging private-sector deployment—while signaling an export-forward stance that positions American AI to compete globally.
Video created by Grok via an image created by Copilot 11/12/2025Continue reading →
Thomas Claburn1 reports that “The 339 respondents participating in the [Murphy et al.2] project – AI and ML scientists, economists, technical staff at frontier AI companies, and policy experts from NGOs – believe that AI will spur significant social changes by 2040.” Claburn says the project found that “there’s only about a 20 to 25 percent chance that the AI train will be slowed by lack of AI literacy, societal unease, lack of use cases, and costs. Data quality, regulations, and cultural resistance are seen as more likely (30 to 35 percent) barriers to adoption. Integration and unreliability are expected to be the most significant obstacles (40 percent).”
MicroAdapt is a new approach to edge artificial intelligence developed at The University of Osaka’s Institute of Scientific and Industrial Research (SANKEN). At its core, MicroAdapt is a family of self-evolving, dynamic modeling algorithms designed to watch time-evolving data streams on small devices, automatically identify recurring regimes or patterns in that stream, and maintain — on device — a compact ensemble of tiny models that are created, updated, and retired as the situation demands. In other words, rather than shipping raw data to the cloud and relying on a single large model trained offline, MicroAdapt performs continual modeling and short-term forecasting in situ on modest hardware such as a Raspberry Pi, using very little memory and power. This on-device learning architecture is what the research team describes as “self-evolving” edge AI. (sanken.osaka-u.ac.jp)
Yasuko Matsubara, Institute of Scientific and Industrial Research, University of Osaka
The research paper by Kestin, Miller, Klales and colleagues* represents a watershed moment in educational technology research, offering rigorously controlled evidence that properly designed AI tutoring can surpass traditional pedagogical best practices. Conducted at Harvard University during Fall 2023 and published on 3 June 2025 in Scientific Reports, this randomized controlled trial provides empirical validation for claims about artificial intelligence’s transformative potential in education.
Introduction: I asked Claude to report on articles published in 2025 that discuss why banning AI chatbots is impossible or unwise in college settings. It found four. I also asked ChatGPT to add two more. -js
By Michael Akuchie English Composition Instructor Southern Illinois University Carbondale
The United States has a reading problem, and according to findings by the National Endowment for the Arts (NEA), it is not wrong to worry about the future of classroom learning and the culture of reading for pleasure. Per the NEA’s survey of US adults who read books in 2022, only 48.5% said that they had read a book within that period. When asked about literary works, such as novels and short story collections, the percentage of adults who reported having consumed at least one literary piece declined to 37.6%. As adults pay less attention to books, especially literary works, that apathy has unfortunately trickled down to first-year college students, who represent the future of America’s labor force.
Introduction: Anna Lee Mijares, in her article “10 AI Innovations Businesses Need to Watch for Competitive Advantage in 2025” (Unity-Connect, 6 Nov. 2025), mentions 10 innovations* that will shape AI in the remainder of 2025. Her list is excellent! She covers 10 of the most important. To complement her work, I asked a number of AI chatbots: Can you think of one or two critical innovations that could be added to her list? All responded with two suggestions, and I combined them into the list below. -js
The question of whether an AI-driven robot can truly play a musical instrument—especially at a high artistic level—touches both the limits of robotics and the nature of human expressivity. In recent years, advances in machine learning, sensor technology, and robotics have brought us closer to answering that question with an emphatic “yes”—but with important qualifications. Some instruments lend themselves more easily to robotic imitation than others. A closer look at the violin, trumpet, guitar, and drums reveals how the degree of difficulty varies depending on the physical and expressive demands of each instrument.
Introduction: I stumbled upon an article this morning, “AI Unlocks Cosmic Secrets: Revolutionizing Discovery in Physics and Cosmology” (by TokenRing AI, Financial Content, 5 Nov. 2025). I was impressed by both the clear style and even clearer message, but I was intrigued by the “writer” — purportedly an AI. Curious, I asked Copilot to review the article and to dig into TokenRing AI. The following is Copilot’s review. -js
Introduction: Because of fee-walls erected by many if not most higher ed conference organizers, many outstanding papers remain out of sight for the academic community. To see if a chatbot could discover, without circumventing paywalls, some of these gems by relying on sources that aren’t normally crawled by chatbots, I asked Grok to identify five to ten noteworthy papers on AI from conferences held in 2025. It accessed and synthesized information from publicly available proceedings, open-access repositories like arXiv, institutional archives, and conference websites, even when full papers are behind paywalls—often through abstracts, preprints, or shared excerpts that highlight key contributions. Grok came up with seven.* -js
Educational Technology and Change Journal 
