👋 Good Morning! This week’s developments highlight a less visible but increasingly decisive layer of the AI race. While model capability continues to advance, the real leverage is shifting toward who controls access, alignment, and the underlying systems that make AI usable at scale. From a $480M seed round backing a vision of human-centric collaboration, to OpenAI introducing advertising to sustain broader access, to renewed attention on the physical mineral supply chains behind AI hardware, the signal is consistent. AI’s next phase is not being defined solely by breakthroughs in intelligence, but by how intelligence is financed, distributed, and materially supported in the real world.
🚀Humans& Secures $480M Seed at a $4.48B Valuation to Build “Human-Centric” AI
This week’s big AI fundraising news comes from Humans&, a three-month-old startup that just closed a massive $480 million seed round at a $4.48 billion valuation, an eye-watering figure for such an early-stage company. Investors include heavyweights like Nvidia, Jeff Bezos, SV Angel, Google Ventures (GV), and Emerson Collective, underscoring strong venture appetite for next-gen AI plays that emphasize human utility.
The founders’ pedigree reads like a who’s-who of elite AI talent: Anthropic reinforcement learning lead Andi Peng, Google’s seventh employee Georges Harik, former xAI researchers Eric Zelikman and Yuchen He, plus Stanford psychology and CS professor Noah Goodman. The ~20-person team also pulls from OpenAI, Meta, AI2, Reflection and MIT.
What Humans& Says It Will Build
Humans&’s positioning is deliberate: instead of aiming to replace humans, it wants AI that amplifies human collaboration. The company likens its envisioned tools to an “AI version of an instant messaging app” that not only communicates but remembers, requests context from users, and leverages long-term interaction data. To achieve this, they’re prioritizing research in long-horizon and multi-agent reinforcement learning, memory, and user understanding, and tightly coupling that research with product development.
Why It Matters
The size of this seed round, comparable to or exceeding many Series A or even early Series B rounds, signals that investors are still betting heavily on foundational AI startups with ambitious visions and elite teams. It also highlights a broader trend: AI that is meant to work with people, not just automate tasks, is becoming a distinct thesis in the market. Whether Humans& can deliver on this collaboration-centric promise, especially with a first product targeted for launch this year, will be an important signal for where the next wave of AI utility actually lands.
🛠 AI Tools & Updates: OpenAI’s Approach to Advertising and Expanded Access
OpenAI has publicly outlined its strategy for introducing advertising into ChatGPT while expanding broad access to powerful AI tools, a significant shift from the company’s prior subscription-centric business model. The key message is clear: ads will be rolled out only to support wider accessibility and not at the expense of core user trust or answer quality.
Expanded Access With ChatGPT Go
OpenAI is making ChatGPT Go, its lower-cost subscription tier, available globally and in the U.S., priced at $8 per month. This tier now offers messaging, image generation, file uploads, and memory features previously limited or behind paywalls, aimed at reaching more users worldwide.
Advertising Principles and Rollout
In the coming weeks, OpenAI plans to test advertisements in the U.S. for free and Go users, placing them clearly below standard ChatGPT responses. The company emphasizes several guardrails intended to preserve product integrity and trust:
Ads will not influence ChatGPT’s answers. Core responses remain optimized for usefulness, with ads shown separately and clearly labeled.
User conversations remain private. OpenAI commits to never selling conversation data to advertisers. Control over personalization settings and the ability to clear ad-related data are core features.
Choice and control are central. Users will always have the option to avoid ads entirely, either by disabling personalization or by subscribing to ad-free paid tiers like Plus, Pro, or Enterprise.
Ads won’t appear in sensitive contexts such as health or politics, and will initially target only adult accounts.
What This Means for Tools and Workflows
OpenAI’s move reflects a pragmatic business imperative: sustaining broad access to AI tools at scale requires diversified revenue beyond subscriptions. That said, the model hinges on maintaining credibility, ads must be relevant, unobtrusive, and clearly demarcated so that user trust isn’t eroded as AI becomes embedded in both personal and professional workflows.
Broader Implication
This strategy may shape how other AI platforms monetize free usage without compromising the perception that AI outputs are unbiased and user-centric, not driven by commercial incentives. It also signals that advertising is emerging as a viable component of sustainable AI business models, provided it is implemented with transparency and user control at the forefront.
📈Trendlines: Greenland’s Critical Minerals in the AI Supply Chain
Amid the global scramble for advanced technology materials, Greenland’s deposits of rare earth elements and other critical minerals have resurfaced as a geopolitical and strategic focal point, particularly in discussions around competition between the U.S. and China for technological and supply chain advantage.
Why Greenland Matters to Tech and AI Hardware
Greenland is home to untapped deposits of rare earth elements (REEs), minerals that are essential for producing high-performance magnets, semiconductors, and other components integral to advanced electronics, clean energy systems, and AI-related infrastructure. These elements include neodymium and dysprosium, which are used in motors and generators, as well as germanium and gallium, which are critical for semiconductors and fiber-optic systems.
China currently dominates global rare earth production and refining, controlling a disproportionate share of the supply chain that underpins much of the world’s high-tech hardware manufacturing. Greenland’s reserves are seen in Washington and other capitals as a potential alternative source to reduce this dependence — though mineral extraction and processing remain complex and costly.
Strategic and Economic Realities
The U.S. Geological Survey classifies dozens of minerals as critical for economic and national security, and rare earths from Greenland could theoretically contribute to that list if brought into production. However, Greenland has no active rare earth mines today, and the combination of harsh climate, infrastructure deficits, environmental concerns, and logistical barriers means that turning raw deposits into supply chain inputs won’t happen quickly or cheaply.
Experts interviewed in the reporting express caution: even if Greenland holds some of the world’s largest undeveloped REE deposits, the ore grades and extraction economics may not justify the capital expenditure required without substantial government and private investment. That’s why some industry voices argue that Greenland’s value is as much geopolitical leverage as it is an immediate commercial source of materials.
Connection to AI and Tech Supply Chains
For the broader AI and technology sectors, access to reliable sources of rare earths and critical minerals isn’t optional, it’s a material dependency. Components like GPUs, accelerators, and advanced sensors cannot be manufactured without these inputs, meaning supply constraints or geopolitical bottlenecks can ripple outward into technology deployment timelines and cost structures. Greenland’s potential role in diversifying supply chains is therefore important in principle, but in practice will take significant time and investment to materialize.
Bottom Line
Greenland’s critical minerals story reflects the reality that AI leadership is increasingly tied not just to algorithms, but to the physical materials, logistics, and geopolitical relationships that enable hardware production. Securing alternate supply sources is strategically desirable, but it is far from a turnkey solution, and Greenland’s development will require decades of effort, not months of headlines.
🧩 Closing Thought
Taken together, these stories underscore a maturing AI landscape where abstraction gives way to constraints. Humans& reflects investor conviction that the next generation of AI value lies in systems designed around long-term human interaction, not just raw capability. OpenAI’s move toward advertising shows the economic reality of scaling access to powerful tools without restricting them to elite users. And Greenland’s critical minerals remind us that even the most advanced AI ultimately depends on physical inputs that are slow, political, and difficult to scale.
The competitive edge in AI is increasingly determined outside the model itself: in capital structure, distribution choices, trust frameworks, and supply chain resilience. As the industry evolves, success will belong less to those who promise intelligence in the abstract, and more to those who can operate AI sustainably within economic, social, and material limits.