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Anthropic Raises $30B at $380B Valuation: The AI Money Keeps Flowing While Safety Researchers Leave
Anthropic closed a $30 billion Series G funding round at a $380 billion post-money valuation today—the second-largest venture funding deal of all time. The round was led by GIC and Coatue, with participation from Dragoneer, Founders Fund, and others. This valuation nearly doubles Anthropic's previous Series F valuation of $183 billion.
But here's the paradox: Anthropic is raising record capital while its own safety researchers are publicly warning that the world is "in peril" and resigning over internal pressure. On the same day the company announced a historic funding round, the narrative was that safety constraints are becoming expensive, not that they're being prioritized.
What this means for your institution: Anthropic's massive capital raise signals confidence in the market. But the company is now facing the same scale-versus-safety pressures that plague OpenAI. Your bet on Anthropic as the "ethical alternative" may have a shorter shelf life than expected.
Action: Document your current vendor alignment. If Anthropic remains your primary platform choice, understand that rapid growth and safety pressures often conflict. Be prepared to adjust your strategy if the company's priorities shift again.
Anthropic Donates $20M to Super PAC: The AI Companies Are Now Fighting in Congress
Anthropic announced it will donate $20 million to a Super PAC backing AI regulation—a direct political move against OpenAI, which has advocated for less stringent regulatory frameworks. This is not a business strategy. This is a values declaration.
The rivalry between Anthropic and OpenAI has now moved beyond technology and marketing into the political sphere. Both companies have well-funded political groups. Both are lobbying Congress. The question is: which regulatory future do they envision for AI?
Reflection for your institution: Your vendor choice is now entangled with federal policy debates. Anthropic and OpenAI are not just competing for your campus contracts—they're competing for which AI regulation framework becomes law. That regulatory choice will affect what you can and cannot do with AI on your campus.
NYT Op-Ed: AI Companies Are Preying on College Students
A New York Times opinion piece published today argues that AI companies deliberately target college students as a strapped customer base to hook when they are most stressed. Free trials convert to paid subscriptions. Campus use becomes institutional adoption. The strategy is transparent.
The argument is simple: AI companies know college students are time-poor, resource-constrained, and early adopters. They offer free or discounted access to build dependency. By April (the end of the semester), students expect the tool to be available. Institutions then have to decide: pay for campus licenses or let students use the free, ad-supported version?
What this means: Your students are targets of deliberate vendor acquisition strategies. The "free" tools your students use are loss leaders designed to convert into institutional spending.
Immediate action: Audit which AI tools your students are currently using. Ask: Are they using free tiers? Are they signing up for paid subscriptions? Are they using institutional licenses? Document this. It will inform your vendor negotiations and your AI literacy curriculum.
AI-Fueled Chip Shortage Drives Up Smartphone Prices: The Hidden Cost of the AI Buildout
Strong demand for AI chips from Nvidia has caused a global shortage of memory chips, pushing DRAM spot prices up more than 600% in recent months. The result: smartphone and PC prices are rising, smartphone shipments are declining 7-10%, and 2026 is shaping up to be one of the most expensive years ever for consumer electronics.
This is not abstract. Your students buy smartphones and laptops. They pay for these devices or their families do. When chip prices spike, device prices spike. When device prices spike, access equity becomes a crisis. Students who cannot afford new devices fall behind.
What this means: The AI infrastructure buildout is not just affecting data centers and cloud pricing. It's affecting consumer device costs and student access to basic tools.
Action: Talk to your IT department about device provisioning for 2026. Are you prepared for higher device costs? Are you planning to extend device lifecycles? How will you address the equity gap if some students cannot afford new devices?
EdWeek Opinion: AI Makes Students Feel Less Connected
Education Week published an opinion piece arguing that the real concern about AI in education is not plagiarism—it's how AI makes students feel. Research shows that 50% of students agree that using AI in class makes them feel less connected to their teachers and peers.
This shifts the conversation from "is AI cheating?" to "what is AI doing to student belonging and engagement?" The emotional and social dimensions matter. If AI tools are reducing connection and belonging, they're undermining the core value proposition of higher education.
Pedagogical reflection: When you integrate AI into a course, you're not just changing what students learn. You're changing how they feel about the learning experience. You're changing connection, belonging, and engagement.
Question for your faculty: When you use AI in your classroom, are you enhancing connection or reducing it? Are you bringing students closer to the material and to each other, or pushing them further apart?
Try something new today
Student Connection Survey: Invite 3-5 students who are currently using AI tools in multiple classes to a brief conversation. Ask them: How does using AI in class make you feel? Does it bring you closer to your professors and classmates, or push you further away? Do you feel more engaged or less? Document their emotional responses. Use this to inform how you guide faculty on AI integration.
A Final Reflection for Today
February 12 reveals a complex picture: record capital flowing into AI companies, political warfare erupting between OpenAI and Anthropic, AI companies deliberately targeting students, hardware costs rising as a hidden consequence of AI infrastructure spending, and students feeling more disconnected even as AI tools proliferate in classrooms.
The common thread? The AI buildout is having cascading effects far beyond technology. It's affecting regulatory policy, student economics, student emotions, and vendor power dynamics. Your institution cannot operate in isolation from these forces.
The question: Are you leading this transition intentionally, or are you being carried along by market forces you don't fully understand? This week's evidence suggests that intentional leadership requires understanding not just the technology, but the money, the politics, the student experience, and the hidden costs.
Move deliberately today.
HigherEd AI Daily