Nvidia, Eli Lilly announce $1 billion investment in AI drug discovery lab — from finance.yahoo.com by Laura Bratton

AI chipmaker Nvidia (NVDA) and pharmaceutical giant Eli Lilly (LLY) on Monday announced that the two companies would jointly invest $1 billion to create a lab in San Francisco focused on using AI to accelerate drug discovery.

The $1 billion investment will be spent over five years on infrastructure, compute, and talent for the lab. Nvidia’s engineers will work alongside Lilly’s experts in biology, science, and medicine to generate large-scale data and build AI models to advance medicine development. The lab’s work will begin early this year, the companies said.

 

Community colleges are training the next generation of manufacturing workers — from manufacturingdive.com by Michelle No
Rutgers University explored how community colleges are responding to regional workforce training demands. Clark State College and Columbus State Community College are among those leading the way.

One underrated option may hold the most promise for workforce growth: the local community college.

That’s according to a series of reports by The Rutgers Education and Employment Research Center released in October, which examines the “hidden innovative structure” of America’s community colleges.

Community colleges excel in ways conducive to a successful manufacturing career, said Shalin Jyotishi, founder of the Future of Work & Innovation Economy Initiative at think tank New America.

 

At CES 2026, Everything Is AI. What Matters Is How You Use It — from wired.com by Boone Ashworth
Integrated chatbots and built-in machine intelligence are no longer standout features in consumer tech. If companies want to win in the AI era, they’ve got to hone the user experience.

Beyond Wearables
Right now, AI is on your face and arms—smart glasses and smart watches—but this year will see it proliferate further into products like earbuds, headphones, and smart clothing.

Health tech will see an influx of AI features too, as companies aim to use AI to monitor biometric data from wearables like rings and wristbands. Heath sensors will also continue to show up in newer places like toilets, bath mats, and brassieres.

The smart home will continue to be bolstered by machine intelligence, with more products that can listen, see, and understand what’s happening in your living space. Familiar candidates for AI-powered upgrades like smart vacuums and security cameras will be joined by surprising AI bedfellows like refrigerators and garage door openers.


Along these lines, see
live updates from CNET here.


ChatGPT is overrated. Here’s what to use instead. — from washingtonpost.com by Geoffrey A. Fowler
When I want help from AI, ChatGPT is no longer my default first stop.

I can tell you which AI tools are worth using — and which to avoid — because I’ve been running a chatbot fight club.

I conducted dozens of bot challenges based on real things people do with AI, including writing breakup texts and work emailsdecoding legal contracts and scientific researchanswering tricky research questions, and editing photos and making “art.” Human experts including best-selling authors, reference librarians, a renowned scientist and even a Pulitzer Prize-winning photographer judged the results.

After a year of bot battles, one thing stands out: There is no single best AI. The smartest way to use chatbots today is to pick different tools for different jobs — and not assume one bot can do it all.


How Collaborative AI Agents Are Shaping the Future of Autonomous IT — from aijourn.com by Michael Nappi

Some enterprise platforms now support cross-agent communication and integration with ecosystems maintained by companies like Microsoft, NVIDIA, Google, and Oracle. These cross-platform data fabrics break down silos and turn isolated AI pilots into enterprise-wide services. The result is an IT backbone that not only automates but also collaborates for continuous learning, diagnostics, and system optimization in real time.


Nvidia dominated the headlines in 2025 — these were its 15 biggest events of the year — from finance.yahoo.com by Daniel Howley

It’s difficult to think of any single company that had a bigger impact on Wall Street and the AI trade in 2025 than Nvidia (NVDA).

Nvidia’s revenue soared in 2025, bringing in $187.1 billion, and its market capitalization continued to climb, briefly eclipsing the $5 trillion mark before settling back in the $4 trillion range.

There were plenty of major highs and deep lows throughout the year, but these 15 were among the biggest moments of Nvidia’s 2025.


 

 

AI working competency is now a graduation requirement at Purdue [Pacton] + other items re: AI in our learning ecosystems


AI Has Landed in Education: Now What? — from learningfuturesdigest.substack.com by Dr. Philippa Hardman

Here’s what’s shaped the AI-education landscape in the last month:

  • The AI Speed Trap is [still] here: AI adoption in L&D is basically won (87%)—but it’s being used to ship faster, not learn better (84% prioritising speed), scaling “more of the same” at pace.
  • AI tutors risk a “pedagogy of passivity”: emerging evidence suggests tutoring bots can reduce cognitive friction and pull learners down the ICAP spectrum—away from interactive/constructive learning toward efficient consumption.
  • Singapore + India are building what the West lacks: they’re treating AI as national learning infrastructure—for resilience (Singapore) and access + language inclusion (India)—while Western systems remain fragmented and reactive.
  • Agentic AI is the next pivot: early signs show a shift from AI as a content engine to AI as a learning partner—with UConn using agents to remove barriers so learners can participate more fully in shared learning.
  • Moodle’s AI stance sends two big signals: the traditional learning ecosystem in fragmenting, and the concept of “user sovereignty” over by AI is emerging.

Four strategies for implementing custom AIs that help students learn, not outsource — from educational-innovation.sydney.edu.au by Kria Coleman, Matthew Clemson, Laura Crocco and Samantha Clarke; via Derek Bruff

For Cogniti to be taken seriously, it needs to be woven into the structure of your unit and its delivery, both in class and on Canvas, rather than left on the side. This article shares practical strategies for implementing Cogniti in your teaching so that students:

  • understand the context and purpose of the agent,
  • know how to interact with it effectively,
  • perceive its value as a learning tool over any other available AI chatbots, and
  • engage in reflection and feedback.

In this post, we discuss how to introduce and integrate Cogniti agents into the learning environment so students understand their context, interact effectively, and see their value as customised learning companions.

In this post, we share four strategies to help introduce and integrate Cogniti in your teaching so that students understand their context, interact effectively, and see their value as customised learning companions.


Collection: Teaching with Custom AI Chatbots — from teaching.virginia.edu; via Derek Bruff
The default behaviors of popular AI chatbots don’t always align with our teaching goals. This collection explores approaches to designing AI chatbots for particular pedagogical purposes.

Example/excerpt:



 

Agents, robots, and us: Skill partnerships in the age of AI — from mckinsey.com by Lareina Yee, Anu Madgavkar, Sven Smit, Alexis Krivkovich, Michael Chui, María Jesús Ramírez, and Diego Castresana
AI is expanding the productivity frontier. Realizing its benefits requires new skills and rethinking how people work together with intelligent machines.

At a glance

  • Work in the future will be a partnership between people, agents, and robots—all powered by AI. …
  • Most human skills will endure, though they will be applied differently. …
  • Our new Skill Change Index shows which skills will be most and least exposed to automation in the next five years….
  • Demand for AI fluency—the ability to use and manage AI tools—has grown sevenfold in two years…
  • By 2030, about $2.9 trillion of economic value could be unlocked in the United States…

Also related/see:



State of AI: December 2025 newsletter — from nathanbenaich.substack.com by Nathan Benaich
What you’ve got to know in AI from the last 4 weeks.

Welcome to the latest issue of the State of AI, an editorialized newsletter that covers the key developments in AI policy, research, industry, and start-ups over the last month.


 

Simon Laveuve’s Scaled-Down Tableaux Reveal Post-Apocalyptic Lifestyles — from thisiscolossal.com by Simon Laveuve and Kate Mothes


Bringing High School Students and Kindergartners Together to Make Art — from edutopia.org by Cory Desmond
A look at how teachers can have students collaborate across grades on an art project that promotes creativity and teamwork.

What happens when high school students and kindergartners collaborate? Art. Innovation. Growth. And so much more.

Inspired by illustrator Mica Angela Hendricks’s collaborations with her 4-year-old daughter—in which Hendricks would begin by drawing a portrait and then have her daughter add to it—I formalized the concept into an inter-grade art lesson. It’s a replicable, three-stage project based on vertical collaboration. This model bridges the creative and social gap between students, weaving together technical skill and imagination through methods based in social and emotional learning (SEL).

It operates by passing a structured project back and forth, compelling older students to engage with empathy, relationship maintenance, and responsible decision-making. Simultaneously, it empowers younger students, giving them significant creative autonomy through their own responsible choices. By breaking down the separation between age groups, cross-grade collaborations cultivate essential skills in ways that isolated classrooms typically can’t.

In this article, I’ll provide a flexible framework for vertical collaboration—a blueprint that teachers can adapt for their own cross-grade collaborations.

 

Could Your Next Side Hustle Be Training AI? — from builtin.com by Jeff Rumage
As automation continues to reshape the labor market, some white-collar professionals are cashing in by teaching AI models to do their jobs.

Summary: Artificial intelligence may be replacing jobs, but it’s also creating some new ones. Professionals in fields like medicine, law and engineering can earn big money training AI models, teaching them human skills and expertise that may one day make those same jobs obsolete.


DEEP DIVE: The AI user interface of the future = Voice — from theneurondaily.com by Grant Harvey
PLUS: Gemini 3.0 and Microsoft’s new voice features

Here’s the thing: voice is finally good enough to replace typing now. And I mean actually good enough, not “Siri, play Despacito” good enough.

To Paraphrase Andrej Karpathy’s famous quote, “the hottest new programming language is English”, in this case, the hottest new user interface is talking.

The Great Convergence: Why Voice Is Having Its Moment
Three massive shifts just collided to make voice interfaces inevitable.

    1. First, speech recognition stopped being terrible. …
    2. Second, our devices got ears everywhere. …
    3. Third, and most importantly: LLMs made voice assistants smart enough to be worth talking to. …

Introducing group chats in ChatGPT — from openai.com
Collaborate with others, and ChatGPT, in the same conversation.

Update on November 20, 2025: Early feedback from the pilot has been positive, so we’re expanding group chats to all logged-in users on ChatGPT Free, Go, Plus and Pro plans globally over the coming days. We will continue refining the experience as more people start using it.

Today, we’re beginning to pilot a new experience in a few regions that makes it easy for people to collaborate with each other—and with ChatGPT—in the same conversation. With group chats, you can bring friends, family, or coworkers into a shared space to plan, make decisions, or work through ideas together.

Whether you’re organizing a group dinner or drafting an outline with coworkers, ChatGPT can help. Group chats are separate from your private conversations, and your personal ChatGPT memory is never shared with anyone in the chat.




 

New Study: Business As Usual Could Doom Dozens Of New England Colleges — from forbes.com by Michael B. Horn

The cause of the challenges isn’t one single factor, but a series of pressures from demographic changes, shifts in the public’s perception of higher education’s value, rising operating costs, emerging alternatives to traditional colleges, and, of late, changes in federal policies and programs. The net effect is that many institutions are much closer to the brink of closure than ever before.

What’s daunting is that flat enrollment is almost certainly an overly optimistic scenario.

If enrollment at the 44 schools falls by 15 percent over the next four years and business proceeds as usual, then 28 of the schools will have less than 10 years of cash and unrestricted quasi-endowments before they would become insolvent—assuming no major cuts, additional philanthropy, new debt, or asset sales. Fourteen would have less than five years before insolvency.

Also see:

From DSC:
The cultures at many institutions of traditional higher education will make some of the necessary changes and strategies (that Michael and Steven discuss) very hard to make. For example, to merge with another institution or institutions. Such a strategy could be very challenging to implement, even as alternatives continue to emerge.

 

How Coworking Spaces Are Becoming The Learning Ecosystems Of The Future — from hrfuture.net

What if your workspace helped you level up your career? Coworking spaces are becoming learning hubs where skills grow, ideas connect, and real-world education fits seamlessly into the workday.

Continuous learning has become a cornerstone of professional longevity, and flexible workspaces already encourage it through workshops, talks, and mentoring. Their true potential, however, may lie in becoming centers of industry-focused education that help professionals stay adaptable in a rapidly changing world of work.
.


.

What if forward-thinking workspaces and coworking centers became hubs of lifelong learning, integrating job-relevant training with accessible, real-world education?

For coworking operators, this raises important questions: Which types of learning thrive best in these environments, and how much do the design and layout of a space influence how people learn?

By exploring these questions and combining innovative programs with cutting-edge technology aligned to the future workforce, could coworking spaces ultimately become the classrooms of tomorrow?

 

KPMG wants junior consultants to ditch the grunt work and hand it over to teams of AI agents — from businessinsider.com by Polly Thompson

The Big Four consulting and accounting firm is training its junior consultants to manage teams of AI agents — digital assistants capable of completing tasks without human input.

“We want juniors to become managers of agents,” Niale Cleobury, KPMG’s global AI workforce lead, told Business Insider in an interview.

KPMG plans to give new consulting recruits access to a catalog of AI agents capable of creating presentation slides, analyzing data, and conducting in-depth research, Cleobury said.

The goal is for these agents to perform much of the analytical and administrative work once assigned to junior consultants, allowing them to become more involved in strategic decisions.


From DSC:
For a junior staff member to provide quality assurance in working with agents, an employee must know what they’re talking about in the first place. They must have expertise and relevant knowledge. Otherwise, how will they spot the hallucinations?

So the question is, how can businesses build such expertise in junior staff members while they are delegating things to an army of agents? This question applies to the next posting below as well. Having agents report to you is all well and good — IF you know when the agents are producing helpful/accurate information and when they got things all wrong.


This Is the Next Vital Job Skill in the AI Economy — from builtin.com by Saurabh Sharma
The future of tech work belongs to AI managers.

Summary: A fundamental shift is making knowledge workers “AI managers.” The most valuable employees will direct intelligent AI agents, which requires new competencies: delegation, quality assurance and workflow orchestration across multiple agents. Companies must bridge the training gap to enable this move from simple software use to strategic collaboration with intelligent, yet imperfect, systems.

The shift is happening subtly, but it’s happening. Workers are learning to prompt agents, navigate AI capabilities, understand failure modes and hand off complex tasks to AI. And if they haven’t started yet, they probably will: A new study from IDC and Salesforce found that 72 percent of CEOs think most employees will have an AI agent reporting to them within five years. This isn’t about using a new kind of software tool — it’s about directing intelligent systems that can reason, search, analyze and create.

Soon, the most valuable employees won’t just know how to use AI; they’ll know how to manage it. And that requires a fundamentally different skill set than anything we’ve taught in the workplace before.


AI agents failed 97% of freelance tasks; here’s why… — from theneurondaily.com by Grant Harvey

AI Agents Can’t Actually Do Your Job (Yet)—New Benchmark Reveals The Gap

DEEP DIVE: AI can make you faster at your job, but can only do 2-3% of jobs by itself.

The hype: AI agents will automate entire workflows! Replace freelancers! Handle complex tasks end-to-end!

The reality: a measly 2-3% completion rate.

See, Scale AI and CAIS just released the Remote Labor Index (paper), a benchmark where AI agents attempted real freelance tasks. The best-performing model earned just $1,810 out of $143,991 in available work, and yes, finishing only 2-3% of jobs.



 

“OpenAI’s Atlas: the End of Online Learning—or Just the Beginning?” [Hardman] + other items re: AI in our LE’s

OpenAI’s Atlas: the End of Online Learning—or Just the Beginning? — from drphilippahardman.substack.com by Dr. Philippa Hardman

My take is this: in all of the anxiety lies a crucial and long-overdue opportunity to deliver better learning experiences. Precisely because Atlas perceives the same context in the same moment as you, it can transform learning into a process aligned with core neuro-scientific principles—including active retrieval, guided attention, adaptive feedback and context-dependent memory formation.

Perhaps in Atlas we have a browser that for the first time isn’t just a portal to information, but one which can become a co-participant in active cognitive engagement—enabling iterative practice, reflective thinking, and real-time scaffolding as you move through challenges and ideas online.

With this in mind, I put together 10 use cases for Atlas for you to try for yourself.

6. Retrieval Practice
What:
Pulling information from memory drives retention better than re-reading.
Why: Practice testing delivers medium-to-large effects (Adesope et al., 2017).
Try: Open a document with your previous notes. Ask Atlas for a mixed activity set: “Quiz me on the Krebs cycle—give me a near-miss, high-stretch MCQ, then a fill-in-the-blank, then ask me to explain it to a teen.”
Atlas uses its browser memory to generate targeted questions from your actual study materials, supporting spaced, varied retrieval.




From DSC:
A quick comment. I appreciate these ideas and approaches from Katarzyna and Rita. I do think that someone is going to want to be sure that the AI models/platforms/tools are given up-to-date information and updated instructions — i.e., any new procedures, steps to take, etc. Perhaps I’m missing the boat here, but an internal AI platform is going to need to have access to up-to-date information and instructions.


 

At the most recent NVIDIA GTC conference, held in Washington, D.C. in October 2025, CEO Jensen Huang announced major developments emphasizing the use of AI to “reindustrialize America”. This included new partnerships, expansion of the Blackwell architecture, and advancements in AI factories for robotics and science. The spring 2024 GTC conference, meanwhile, was headlined by the launch of the Blackwell GPU and significant updates to the Omniverse and robotics platforms.

During the keynote in D.C., Jensen Huang focused on American AI leadership and announced several key initiatives.

  • Massive Blackwell GPU deployments: The company announced an expansion of its Blackwell GPU architecture, which first launched in March 2024. Reportedly, the company has already shipped 6 million Blackwell chips, with orders for 14 million more by the end of 2025.
  • AI supercomputers for science: In partnership with the Department of Energy and Oracle, NVIDIA is building new AI supercomputers at Argonne National Laboratory. The largest, named “Solstice,” will deploy 100,000 Blackwell GPUs.
  • 6G infrastructure: NVIDIA announced a partnership with Nokia to develop a U.S.-based, AI-native 6G technology stack.
  • AI factories for robotics: A new AI Factory Research Center in Virginia will use NVIDIA’s technology for building massive-scale data centers for AI.
  • Autonomous robotaxis: The company’s self-driving technology, already adopted by several carmakers, will be used by Uber for an autonomous fleet of 100,000 robotaxis starting in 2027.


Nvidia and Uber team up to develop network of self-driving cars — from finance.yahoo.com by Daniel Howley

Nvidia (NVDA) and Uber (UBER) on Tuesday revealed that they’re working to put together what they say will be the world’s largest network of Level 4-ready autonomous cars.

The duo will build out 100,000 vehicles beginning in 2027 using Nvidia’s Drive AGX Hyperion 10 platform and Drive AV software.


Nvidia stock hits all-time high, nears $5 trillion market cap after slew of updates at GTC event — from finance.yahoo.com by Daniel Howley

Nvidia (NVDA) stock on Tuesday rose 5% to close at a record high after the company announced a slew of product updates, partnerships, and investment initiatives at its GTC event in Washington, D.C., putting it on the doorstep of becoming the first company in history with a market value above $5 trillion.

The AI chip giant is approaching the threshold — settling at a market cap of $4.89 trillion on Tuesday — just months after becoming the first to close above $4 trillion in July.


 

Resilient by Design: The Future of America’s Community Colleges — from aacc.nche.edu

This report highlights several truths:

  • Leadership capacity must expand. Presidents and leaders are now expected to be fundraisers, policy navigators, cultural change agents, and data-informed strategists. Leadership can no longer be about a single individual—it must be a team sport. AACC is charged with helping you and your teams build these capacities through leadership academies, peer learning communities, and practical toolkits.
  • The strength of our network is our greatest asset. No college faces its challenges alone, because within our membership there are leaders who have already innovated, stumbled, and succeeded. Resilient by Design urges AACC to serve as the connector and amplifier of this collective wisdom, developing playbooks and scaling proven practices in areas from guided pathways to artificial intelligence to workforce partnerships.
  • Innovation in models and tools is urgent. Budgets must be strategic, business models must be reimagined, and ROI must be proven—not only to funders and policymakers, but to the students and communities we serve. Community colleges must claim their role as engines of economic vitality and social mobility, advancing both immediate workforce needs and long-term wealth-building for students.
  • Policy engagement must be deepened. Federal advocacy remains essential, but the daily realities of our institutions are shaped by state and regional policy. AACC will increasingly support members with state-level resources, legislative templates, and partnerships that equip you to advocate effectively in your unique contexts.
  • Employer engagement must become transformational. Students deserve not just degrees, but careers. The report challenges us to create career-connected colleges where employers co-design curricula, offer meaningful work-based learning, and help ensure graduates are not just prepared for today’s jobs but resilient for tomorrow’s.
 

Entrepreneurship: The New Core Curriculum — from gettingsmart.com by Tom Vander Ark

Key Points

  • Entrepreneurship education fosters resilience, creativity, and financial literacy—skills critical for success in an unpredictable, tech-driven world.
  • Programs like NFTE, Junior Achievement, and Uncharted Learning empower students by offering real-world entrepreneurial experiences and mentorship.

“Entrepreneurship is the job of the future.”

— Charles Fadel, Education for the Age of AI

This shift requires a radical re-evaluation of what we teach. Education leaders across the country are realizing that the most valuable skill we can impart is not accounting or marketing, but the entrepreneurial mindset. This mindset—built on resilience, creative problem-solving, comfort with ambiguity, and the ability to pivot—is essential in startups, as an intrapreuer in big organizations, or as a citizen working for the common good.

 

From siloed tools to intelligent journeys: Reimagining learning experience in the age of ‘Experience AI’ — from linkedin.com by Lev Gonick

Experience AI: A new architecture of learning
Experience AI represents a new architecture for learning — one that prioritizes continuity, agency and deep personalization. It fuses three dimensions into a new category of co-intelligent systems:

  • Agentic AI that evolves with the learner, not just serves them
  • Persona-based AI that adapts to individual goals, identities and motivations
  • Multimodal AI that engages across text, voice, video, simulation and interaction

Experience AI brings learning into context. It powers personalized, problem-based journeys where students explore ideas, reflect on progress and co-create meaning — with both human and machine collaborators.

 
© 2025 | Daniel Christian