Anthropic, Google and Meta have hired computer scientists, neuroscientists and philosophers to study what some in the industry think may become a moral crisis. “We keep finding things that are mysterious, even unsettling,” Olah said of Anthropic’s AI systems. “We find evidence of introspection [and] states that functionally mirror joy, satisfaction, fear, grief and unease.” (Leo took a different stance, writing that “so-called artificial intelligences do not undergo experiences.”) Meta’s chief AI officer, Alexandr Wang, recently said the company wants to be nice to its AI creations. “One of the things that we really care about is how can we develop the models and deploy the models in a way that is thoughtful about their subjective feeling,” he said on the “Core Memory” podcast. Neuroscientists and brain experts are generally skeptical that today’s AI models are or could soon be conscious.
Monday, July 13, 2026
The AI Lane to Watch - Matt Wolfe, Future Tools
Large Language Models (the ones powering ChatGPT, Claude, Gemini) are trained on text. They predict the next word in a sentence—great for writing, summarizing, and reasoning over language.
Large Quantitative Models are trained on numerical data and scientific equations from real-world lab experiments. They predict things like how strongly a molecule binds to a catalyst surface, or which drug candidates are worth testing in the lab, making them useful for non-text use cases.
LQMs are already integrated with Claude, and now they’re coming to Gemini. The first two models hitting Google Cloud Marketplace are AQCat (Q3 2026, for materials and catalyst discovery: think batteries, semiconductors, sustainable fuels) and AQPotency (later this year, for drug discovery). Researchers can prompt in plain English and have Gemini hand off the actual scientific calculations to a physics-grounded model underneath. The pattern is basically: LLMs as the interface, LQMs as the engine.
Sunday, July 12, 2026
The seven operating truths of AI-native companies - McKinsey
These are not isolated experiments. Over the past several months, we have met with the tech and business leaders at 15 AI-centric companies—spanning continents, industries, and stages of development, from four-person start-ups to established global platforms—to learn what it takes to make AI capabilities truly deliver. We expected to hear 15 different stories. Instead, this diverse group of businesses, independent of one another, seemed to converge on the same fundamental insights about what it takes to successfully place AI at the center of the organization. That convergence is the story.
Will AI in education succeed? - Brad Olsen and Jobin Thomas, Brookings
In May 1959, the first PLATO (Programmed Logic for Automated Teaching Operations) system was unveiled at the University of Illinois. This means that last month was the 67th anniversary of the birth of Computer-Assisted Instruction (CAI). Such an event merits a look at technology in education today. Many people are currently either for or against generative artificial intelligence (AI) in education—a stark binary that misses the complexity and inevitability of the current technological revolution. The success or failure of using technology for education (EdTech) is only partly about the technology itself. What matters more are the conditions underlying EdTech. EdTech is a tool, not a standalone solution, and without a proper support system in place, it will not succeed.
Saturday, July 11, 2026
I landed a Big Tech AI job. Treating my career like a science lab helped me overcome my fear of learning - As told to Charissa Cheong, Business Insider
This as-told-to essay is based on a conversation with Nitya Kumar, 25, an Adobe employee who lives in India. The following has been edited for length and clarity. I landed a product design role at Meta straight out of college in 2022. By 2024, I saw the industry pivoting toward AI and wanted to learn new AI design skills. During this process, I stopped seeing my career as a ladder with a focus on moving upward. In my view, all work and no play keeps the Big Tech offers away, so I started treating my career like a science lab, giving myself the freedom to experiment. This helped me overcome my fear of learning a new technology and land a role working with AI at Adobe.
AI Skills Gap: What Industries Are Hiring AI Talent in 2026 - Boston University
The hardest part of the AI boom is no longer building the technology. It is finding people who can put it to work. Across nearly every sector, demand for AI talent is running well ahead of supply, and the gap is reshaping who gets hired, what they are paid, and which skills are worth investing in. If you are weighing a move into AI, that imbalance is the opportunity. Here is where the demand is concentrated in 2026, what those roles pay, and how to choose a path that fits the industry you are in or the one you want to enter.
Friday, July 10, 2026
Stanford graduates rethink their futures as AI transforms tech - Lily Jamali, BBC
Stanford occupies a unique position in the American tech ecosystem. It's regarded as a hotbed of innovation and resides in the shadow of some of the most influential Big Tech companies on the planet, including many pioneers in the AI field. Its elite students enter the job market with an undeniable edge. Yet even there, the backlash was inescapable. The BBC spoke to Stanford graduates shortly after Pichai finished his address and they expressed a wide range of views on AI. Some are scared. Some are excited. But nearly everyone agrees that AI is already changing the world around them, whether they like it or not.
Teaching, AI, and the Human Core of Education : The Future Worth Defending - Armand Doucet
For teachers, their unions, and the policymakers who shape the conditions in which they work, the question is no longer whether AI will shape education, but how that shaping will be governed. The purpose of this report is to take stock of that reality: to identify what has changed, what remains essential, and what education systems must now do differently if AI is to be integrated responsibly, based on needs and governed in the public interest. Its central claim is straightforward. AI is not disrupting the purpose of education. It is disrupting the conditions under which that purpose can be realized. What follows therefore examines what has changed, what has not, and what must now be intentionally rebuilt, protected, and governed.
Thursday, July 09, 2026
International Perspectives on AI in Higher Education - University of Bonn
Artificial intelligence is rapidly becoming a key factor in higher education, opening up new possibilities for learning, teaching and examinations while also leaving universities grappling with fundamental strategic, ethical and organizational questions. Hosted by the University of Bonn from June 10 to 12, 2026, the annual summit of the Global Universities for Societal Impact (GUSI) international network focused on how higher-education institutions can shape this change responsibly. Representatives from the five partner universities debated how AI is transforming research and teaching and what answers higher-education institutions need to find to address these trends.
Examining the influence of AI in higher education - Amy Juravich, WOSU
Last year, the California State University System entered into a contract with OpenAI to provide students, faculty and staff with ChatGPT Edu. The contract was recently renewed despite many students and professor encouraging the university not to continue the deal. Just recently, here in Ohio, the University of Cincinnati did the same, offering BearcatGPT to all their students and faculty for free. Ohio State University is no exception. The AI Fluency initiative is in full swing and has recently broadened into the Arts and Humanities AI Institute. Should universities conform to AI in academic spaces? What are the potential negative consequences of AI use in higher education?
Wednesday, July 08, 2026
‘RAISE US’ Is a Rare Positive Development in AI Transformation - Ray Schroeder, Inside Higher Ed
Remarkably, in this highly partisan era of American history, there is a newly formed, nonpartisan association with the stated purpose of “partnering with governors, employers and training partners to help the American workforce make a successful transition to an AI economy.” This is the first large-scale, independent entity formed to address the challenge that is top of mind of many of us in higher education and associated fields who are concerned with the anticipated impact of artificial intelligence on the workforce. It is good news!
OpenAI Has New AI Models. Here’s Why You Can’t Use Them - Maxwell Zeff, Wired
The White House asked OpenAI to delay the rollout of its GPT-5.6 AI models, two weeks after Anthropic had to take its most advanced AI models offline. OpenAI is delaying the public release of its next generation of AI models, GPT-5.6, at the request of Trump’s White House, the company confirmed on Friday. OpenAI said it would first share the models with a small set of customers, which will be preapproved by the US government. It will then work with the administration to slowly expand access.
https://www.wired.com/story/openai-gpt-56-model-release-trump-admin-approval/
Tuesday, July 07, 2026
9 Free "AI Skills" and "Plug-ins" That Feel Like Cheat Codes - Matt Wolfe, YouTube
In this video, creator Matt Wolfe breaks down how to leverage "skills" and "plugins"—which are essentially reusable instruction files, advanced prompts, or bundled configurations—across popular AI developer environments and agent harnesses like OpenAI's Codeex and Anthropic's Claude Code. Instead of just adding context, these free tools instill repeatable, specialized behaviors in an AI agent. Wolfe highlights a variety of practical tools, starting with GStack from Y Combinator's Gary Tan, which transforms an AI into an entire virtual engineering team. He also highlights Stop Slop for stripping out generic "AI-isms" from text, and Last 30 Days for running deep, real-time sentiment research across the web. The video also explores highly visual and creative AI utilities. Wolfe demonstrates Graphify and Understand Anything, two tools that map complex codebases or personal knowledge databases into queryable, interactive knowledge graphs to significantly lower token costs and improve engineering onboarding. Finally, he compares specialized aesthetic enhancers like Anthropic's Front-End Design and the Taste skill for UI refinement, alongside animation tools like Remotion and HeyGen's Hyperframes, which write code to automatically generate motion graphics, video charts, and logo reveals from simple text prompts. [assistance with summary by Gemini Flash]
The symbiotic enterprise - McKinsey
The symbiotic enterprise - McKinsey
At scale, this transformation gives rise to a new enterprise model: the symbiotic enterprise, in which humans, AI agents, and intelligent robots each contribute according to their respective strengths within flatter organizations and under a new economic model, with technology becoming a primary cost driver. Beyond productivity, the symbiotic enterprise fundamentally changes the economics of growth by enabling organizations to innovate faster, adapt continuously, unlock new revenue opportunities, and scale through software rather than labor. Traditional advantages such as expertise, workforce scale, coordination complexity, and market frictions erode, lowering barriers to entry and enabling customer re-insourcing and AI-native competitors to challenge incumbents.
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