AI Is Already Here: Are We Preparing Our Students?
The ultimate educational challenge is preparing students to become seamlessly integrated human-AI hybrid beings who can think, learn, and create at superhuman levels
I don’t think there is anything a “regular” person can do to slow down the advancement of the AI industrial era.
Some find that attitude to be wrong and think it leads to uncritical adoption. But thinking trhat that also won’t slow development and adoption.
This doesn’t mean that I think AI is only good.
I have signficant concerrns about AI. Mostly, I worry that AI will lead to the econommic devaluation many people and that that when people are seen as having little economic value they become expendable. Economic leverage may have also been what really triggered the growth of democracy. Without individual economic leverage, we may lose democracy.
But, again, these concerns don’t deny the reality of AI’s advances. What they do is put a premium on helping students and adults mantain economic relevance.
Data Centers
Meta is planning a 1 million GPU data center that size of Manhattan. xAI already has a 200,000 GPU data center in Tennesse and is in the process of expanding it to a 320,000 GPU center to support video training. Some argue it will become a 1 million GPU center. This is in addition to “Stargate” and all of the other data centers being built in the US and world wide. Billions is being poured into Pittsburgh to develop AI and energy resources.
China is also building hundreds of data centers. Big tech companies are investing billions in developing energy resources needed to power the data centers.
Valuations
Anthropic is pushing a $100 billion evaluation. Open AI — $300 billion. NVIDIA just hit $4 trillion.
Thinking Machines, a start-up that doesn’t even have a product — $12 billion. Safe SuperIntelligence, another company without a public product, is valued at $32 billion.
That’s just a few.
AGI
I agree with the general sentiment that the AGI focus is bad, as there isn’t a precise agreed-upon definition and regardless of whether or not is obtained based on certain definitions, there will continue to be strong advances and what we already have will radically impact the economy as more and more moves into the application layer.
Gerry White even makes the claim that Grok4 may have “quietly crossed the line” into AGI because it can “reason, reflect, and retain context.” Many (Eric Schmidt, others) think that by the end of the year AI systems will essentially have infinite memory.
Thinking Machines is building a multi model that will be released in the next couple of months that that “chats, sees and works the way people actually collaborate.”
As Elon Musk acknowledges, these AIs still need to be able to invent new things, something he says is likely within a year and we can see glimpses of in AlphaEvolve, and understand the physical world, but we are quickly pushing into significant digital intelligencer, call it what you wish.
Robotics
$80 million for AI construction equipment that will work around the clock building homes without any humans.
Fully autonomous farms are under development.
Delivery robots are riding the subway in Shenzhen.
Sectors
AI is already transforming sectors of the economy, including, as noted, construction.
Companionship and Counselling. As I’ve noted, companionship and counselling are currently the #1 use case for generative AI. A few days ago, Musk released Grok’s controversial anime NWSF characters and is hiring engineers to build more.
Health care. There have been huge breakthroughs in health care, with Google’s Isomorphic Labs preparing to launch human trials of AI-designed drugs, marking a significant milestone in AI-powered pharmaceutical development.
Microsoft has introduced the AI Diagnostic Orchestrator (MAI-DxO), a sophisticated system that achieved remarkable results in diagnostic accuracy. In testing on 304 complex case studies from the New England Journal of Medicine, MAI-DxO correctly diagnosed 85.5% of cases, exceed scores of experienced physicians.
The system operates through a novel "chain of debate" approach, employing five specialized AI agents that work together to investigate diagnostic challenges. These agents include a gatekeeper that controls information release, a diagnostic agent, a test-ordering agent, and agents that develop hypotheses and review results. The system draws on multiple large language models, including OpenAI's GPT, Google's Gemini, Anthropic's Claude, and Meta's Llama, to create what Microsoft describes as "a path to medical superintelligence."
Law. The legal profession is experiencing a significant transformation driven by (AI), with tools like Harvey AI leading the charge.
Harvey distinguishes itself from general AI tools by being specifically trained for legal work. Built on OpenAI's GPT-4 model, Harvey was further trained with general legal data including case law and reference materials. When engaged by a firm, Harvey is then trained by the firm's own work products and templates, essentially providing a personalized legal assistant that understands both general law and the specific practices of each firm.
The company raised $300 million in a Series E funding round at a $5 billion valuation in June 2025, making it one of the highest-valued legal AI startups. This represents a significant jump from its $715 million valuation in December 2023. The company's annualized revenue run rate reached $75 million in April 2025, up from $50 million earlier in the year.
Harvey operates as an invite-only service, and more thousands of law firms are on Harvey's waiting list. This exclusive approach has created significant demand, with the waitlist described as "tight" but growing.
It is reported that Harvey provides incredible advantages to firms. I even saw a solo practitioner post on LinkedIn that it was unfair that she couldn’t gain access (waiting list) because it made it hard to serve her clients in the way that firms with access could.
Finance. Perplexity AI has launched Perplexity Finance, a dedicated financial research platform. The platform provides real-time stock quotes, historical earnings data, industry peer comparisons, and detailed analysis of company financials. What sets Perplexity Finance apart is its ability to combine conversational AI with credible financial data sourced from Financial Modeling Prep (FMP), ensuring data accuracy while maintaining the intuitive interface that Perplexity is known for.
In July 2025, Anthropic launched Claude for Financial Services, marking the company's first major industry-specific AI platform. This represents a significant strategic shift toward vertical AI solutions designed to address specific industry pain points. The platform pairs Anthropic's core enterprise and coding AI tools with information from third-party financial data providers, including FactSet, PitchBook, and Morningstar.
The impact of Claude in financial services has been measurable. Norges Bank Investment Management (NBIM) reported achieving approximately 20% productivity gains, equivalent to 213,000 hours, with portfolio managers and risk departments now able to seamlessly query data warehouses and analyze earnings calls with unprecedented efficiency.
Traditional financial institutions are also making significant AI investments. JPMorgan Chase has rolled out its LLM Suite to more than 60,000 employees, helping them with tasks like writing emails and reports. The bank's AI initiatives have shown remarkable results, with JPMorgan's AI for fraud prediction saving $250 million annually.
Goldman Sachs has launched its GS AI Assistant firmwide, with approximately 10,000 employees already utilizing the tool. The assistant helps with "summarizing complex documents and drafting initial content to performing data analysis," according to internal communications.
Amplifying Intelligence
While much of the AI discourse focuses on AGI and future possibilities, what we're actually witnessing across industries is a powerful form of intelligence amplification—where AI systems enhance and extend human cognitive capabilities in highly specialized ways. The evidence from current deployments reveals how AI is transforming professional work by augmenting human expertise rather than simply automating tasks.
Consider the concrete examples emerging across professional sectors. Harvey AI, trained specifically for legal work and customized to individual firm practices, amplifies lawyers' ability to process case law, draft documents, and navigate complex legal research. The system understands both general legal principles and the specific practices of each firm, essentially providing a personalized legal assistant that enhances rather than replaces professional judgment. Portfolio managers at Norges Bank Investment Management achieved 20% productivity gains using Claude to query data warehouses and analyze earnings calls—tasks that now happen with unprecedented efficiency and depth. Goldman Sachs employees utilize their AI Assistant for document summarization and data analysis, allowing them to focus their expertise on strategic decision-making and client relationships.
Human-Machine Merger and Cognitive Amplification
Beyond professional applications, we're approaching an era of direct cognitive enhancement through wearable and implantable technologies that promise to fundamentally alter human intellectual capacity.
AI-powered smart glasses like the Ray-Ban Meta Smart Glasses are already providing users with instant access to AI assistance, offering real-time translation, information lookup, and contextual analysis of the visual world around them. As Mark Zuckerberg has predicted, not wearing AI glasses in the future may put individuals at a cognitive disadvantage—much like how smartphones transformed information access, these devices are positioning themselves as essential cognitive tools.
Brain-computer interfaces are advancing rapidly, with devices now allowing users to interact with computers, smartphones, and gaming consoles through head movements and blinking, while Neuralink has disclosed that three volunteers have received its N1 implant, which consists of multiple fine electrode threads inserted directly into the brain.
AI-powered brain fitness platforms like BRAIN.ONE are leveraging AI and wearable technology to deliver highly personalized cognitive enhancement strategies, integrating data from multiple sources like wearables to optimize mental performance in real-time. Research into Brain–AI Closed-Loop Systems (BACLoS) has developed wireless earbud-like electroencephalography (EEG) measurement devices that enable human brain wave analysis and transfer results to AI to verify and enhance AI decision-making. These technologies represent a spectrum of cognitive augmentation—from external AI companions that enhance memory and processing speed, to direct neural interfaces that could eventually allow seamless integration between human thought and AI, fundamentally expanding the boundaries of human cognitive capability.
Preparing Students for Radical AI-Human Integration
Educational institutions must fundamentally reimagine their mission around developing students' capacity to use and build intelligence-amplifying technologies as the foundation for deeper human-AI cognitive integration.
The starting point lies in teaching students to masterfully orchestrate AI tools—from basic prompt engineering and AI model evaluation to understanding how to combine multiple AI systems for complex problem-solving.
Students need to become fluent in designing and customizing AI workflows, learning to build specialized AI agents, and developing the technical skills to create new forms of cognitive enhancement. This foundation in AI tool mastery naturally progresses to more intimate forms of human-AI collaboration through wearable and integrated technologies. Students must prepare for a world where AI browsers become cognitive extensions, instantly providing contextual information and analytical insights directly into their thought processes, while AI-powered smart glasses offer real-time translation, object recognition, and augmented reality overlays that enhance perception and decision-making.
The current educational trajectory culminates in preparing students for direct neural integration, where brain-computer interface research is already demonstrating that BCI-based applications can successfully regulate students' cognitive abilities and offer deep understanding of brain mechanisms to improve learning strategies, while recent studies indicate that BCI devices have positive impact on students' attention skills and working memory as well as on other skills, such as visuospatial, social, imaginative and emotional abilities.
Schools need curricula that explore the ethics and mechanics of cognitive augmentation, training students to optimize their brain-AI partnerships, and preparing them for a world where enhanced humans work alongside unenhanced ones.
Future (5-10 years) educational scenarios will include cognitive behavioral detection and intervention for cognitive enhancement, student cognitive assessment and enhancement, and mental health interventions evaluating teaching processes.
The ultimate educational challenge is preparing students to become seamlessly integrated human-AI hybrid beings who can think, learn, and create at superhuman levels while maintaining their essential humanity and agency in an age of cognitive fusion.