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Executive Summary: Human‑Centric Startups Rise Amid AI Money FloodEven as AI fundraising breaks new records, founders like Brynn Putnam are raising capital for ventures that prioritize face‑to‑face interaction and tactile tech. The shift reflects a broader consumer desire for experiences that feel more human, challenging the narrative that all capital must flow to AI‑only companies.Rise of Offline‑First Startups in an AI‑Dominated MarketRecent weeks have highlighted two contrasting movements:Board – founded by Mirror co‑founder Brynn Putnam, secured a new funding round to develop in‑person games and social experiences.Cyberdeck creators – a community building whimsical DIY computers that literally encourage users to "touch grass," gaining viral attention for their analog appeal.Both illustrate a growing appetite for products that foster real‑world connection.Funding Landscape: AI vs Human‑Centric VenturesAlphabet announced an $80 billion AI fundraising commitment, underscoring the scale of corporate AI investment.Anthropic filed a confidential IPO, signaling that even AI‑focused startups are eyeing public markets.Despite this, startups like Board are attracting seed‑stage capital, indicating that investors still see value in non‑AI playbooks.Impact on Consumer Behavior and Startup StrategyThe emergence of "together tech" suggests a market correction:Consumers are gravitating toward experiences that feel tangible and social.Founders are positioning products as antidotes to screen fatigue, leveraging nostalgia and physical interaction.Venture firms are diversifying portfolios to include both AI‑heavy and offline‑first concepts.Looking Ahead: A More Balanced Startup EcosystemAnalysts expect the following trends to shape the next 12‑18 months:Continued inflow of capital into AI, but with a growing slice earmarked for hybrid models that blend digital intelligence with physical experiences.Increased media coverage and podcast discussion (e.g., Equity hosts Kirsten Korosec, Anthony Ha, and Sean O’Kane) will amplify awareness of offline‑first ventures.Potential for strategic partnerships between AI giants and tactile‑tech startups, creating new categories of smart‑physical products.

Across the AI ecosystem, firms from Uber to Priceline are confronting token bills that dwarf their original forecasts, sparking a rush to build visibility, auditability, and guardrails around AI spend. Tokenomics Foundation Aims to Impose Cost Discipline on AI Tokens The Linux Foundation announced the creation of the Tokenomics Foundation, a standards body designed to codify metrics, definitions, and best practices for AI token usage—mirroring the FinOps movement that tamed cloud spend. Executive director J.R. Storment described the climate as an "existential crisis" for many enterprises, with budgets blown out by 3‑fold in early 2026. Escalating Bills Highlight the Scale of the Problem Uber exhausted its entire 2026 AI coding budget by April. Microsoft revoked Claude Code licenses for developers after a rapid cost surge. A Priceline employee reported a routine Cursor contract renewal that was 4‑5× more expensive than prior terms. One unnamed firm allegedly incurred a $500 million Claude bill after failing to set usage limits. Developer surveys from Faros AI show per‑developer token consumption rising 18.6× in nine months. Goldman Sachs projects global token usage to multiply 24‑fold by 2030. Emerging Market of AI Spend Management Tools Start‑ups and established vendors are racing to fill the visibility gap: Pay‑i offers granular tracking, measurement, and optimization of GenAI investments. Paid provides developer‑level cost dashboards and value‑based billing. Platforms such as Jellyfish, Waydev, and Faros AI deliver AI‑agent monitoring to prove ROI. Legacy cloud‑cost players like Ramp, Datadog, and New Relic are adding token‑level observability and GPU monitoring. At the upcoming FinOps X conference, AWS is expected to unveil new financial‑management features for enterprise AI spend. Standardization and Optimization Expected to Shape AI Economics The Tokenomics Foundation plans to release a canonical definition of “tokenomics,” open specifications, and novel metrics such as cost‑per‑intelligence and tokens‑per‑watt. Early adopters like OpenRouter-style model routers already shift queries to cheaper models, a practice that could become industry‑wide. Analysts argue that the greatest ROI will come from moving the broad middle tier of users from low to moderate token consumption rather than encouraging heavy‑use outliers. As Nishant Gupta of Salesforce notes, AI token economics demand a new operational muscle set, and the coming standards may provide the assembly line the industry still lacks.

The Lead: Tech Hub's Resistance to Data Expansion Seattle's city government is on the verge of passing a year-long ban on the construction of new datacenters, making it the largest city yet in the US to consider such a moratorium as nationwide backlash grows. Four companies sought to build five large datacenters in areas serviced by Seattle's public utility; if approved, they would have consumed approximately a third of the city's current daily demand for electricity. The Technical Breakthrough: Seattle's Regulatory Response On Wednesday, city council committees unanimously passed the moratorium and an accompanying resolution. A full council vote on both measures is expected on Tuesday, which activists see as a formality after weeks of engagement with city officials on the topic. Lawmakers cited the two measures as an effort to protect residents from rising utility costs and environmental hazards. They said they plan to spend the duration of the moratorium drafting regulations tailored to the AI industry's massive facilities. The Financial Impact: Energy Consumption and Economic Concerns The proposed datacenters would have consumed approximately a third of Seattle's current daily demand for electricity, raising significant concerns about utility costs and resource allocation. During a moratorium, officials may establish pollution standards, energy connection requirements and contract terms, labor standards, and other rules specific to datacenters. The moratorium and accompanying resolution enable Seattle's public utility to establish separate rates for new "large load" customers, a category that includes large datacenters. The Industry Impact: Tech's Own Backlash The swift response to the proposed datacenters represents a major rebuke in tech's own backyard. A hub for the technology sector, Seattle's metro area serves as the headquarters for Microsoft and Amazon, which have laid off thousands of local workers over the past year as they spend a projected $390bn on AI investments in 2026. Seattle's tech workers have shown up in large numbers to organize against the proposed datacenters, with many viewing AI as synonymous with job losses despite increased productivity. The Regional Implications: Washington State's Precedent Lawmakers and advocates hope Seattle's status as a tech city can encourage more jurisdictions to join the dozens of other local governments moving to regulate datacenters, which are bipartisanly unpopular. Debora Juarez, who chairs the committee overseeing Seattle's public utility, noted that the datacenters' water use could threaten local Indigenous groups' treaty and water rights, which spurred tribes to be among the first to organize against new datacenters. Seattle's tech and climate activists are also working with groups in other parts of Washington state, seeing a Seattle win against datacenters as a replicable regional roadmap. The Future Outlook: Regulatory Uncertainty for AI Infrastructure Seattle mayor Katie Wilson indicated that the pause would allow the city to determine whether datacenters are a "good use of urban land" and potentially draft public benefit requirements, such as requisite investments in affordable housing and transit projects, in exchange for approval. Activists intentionally favored a year-long moratorium over a full-out ban because the former strategy could assemble a larger coalition in its favor, while potentially delivering the same end result. If an AI market bubble bursts in the coming year, the facilities are unlikely to be built, regardless of the moratorium's outcome.

The Director's Digital PivotMartin Scorsese's announcement that he has invested in an AI company and uses the technology to create storyboards has triggered a backlash from fellow members of the film industry.The New York Times reported that Scorsese had been appointed in 2025 as a partner and adviser to Black Forest Labs, a German-based venture that specialises in text-to-image generative AI.Scorsese said in a statement to the New York Times: "I'm interested in the intersection of technology and storytelling, and seeing how that can push the bounds of creativity to create deeper and richer experiences for audiences. Remember, cinema is a young medium, only around 125 years old, so we have to be open to how it can evolve."He added: "For 70 years, I've been creating my own storyboards. There's always been this problem of how do you communicate what you see in your head to your cast and crew. There are some things you have to see and feel. Now with this tool, I can share what I'm visualising more clearly and efficiently to my creative team."The Artist's RebellionStoryboard and concept artists responded angrily, with Karla Ortiz, a concept artist on a string of Marvel films including Black Panther, Avengers: Endgame and Avengers: Infinity War saying on social media: "He throws every single storyboard artist he's ever worked with under the bus ... To use his legacy and power for this is just so disgusting."Samuel Deats, director of animated TV series Castlevania, added on social media: "There is absolutely no reason to need AI built on the stolen work of millions of artists to storyboard your vision, have some damn pride and respect your peers."The AI Wave in HollywoodWith this move, Scorsese has joined the swelling ranks of significant film industry figures who are endorsing and utilising AI. Steven Soderbergh used AI generated sequences in his recent documentary John Lennon: The Last Interview while Jurassic World Rebirth director Gareth Edwards described AI as "a fucking genius at helping you". Tribeca film festival co-founder Jane Rosenthal defended plans to screen Dreams of Violets, a fully AI-generated film about protesters in Iran, saying that "it's something that should be seen right now at this time".The Production RevolutionThere is no suggestion, however, that Scorsese is planning to use gen-AI images in a film, but rather as part of the preparatory process. In his statement he said: "I recently tested this out on a scene, and the ability to visualise and immediately share the storyboard was creatively freeing. During the preproduction process, time costs money, and this allowed us to move faster without sacrificing quality or craft."

The Lead: Uber's AI Budget Crisis AI is getting expensive, and some companies are cutting back on usage in an attempt to moderate costs. That cohort now includes Uber, which recently instituted internal usage caps as a way to cut down on its exorbitant AI spend after blowing through its entire annual budget in just four months. The Event Details: New Spending Caps and Internal Tracking According to Bloomberg, Uber has implemented a new rule that places a monthly $1,500 cap per employee and per agentic coding tool, including Anthropic's Claude Code or Cursor. The usage is trackable via an internal dashboard that each employee has access to. In certain cases, these caps can be exceeded with permission from the company. The Data Analysis: The Financial Impact of AI Adoption The financial implications are significant. In April, Uber's CTO revealed that the ridesharing giant had consumed its entire annual AI budget in a matter of four months. This accelerated spending occurred after Uber encouraged staff to use AI "as much as possible" and even ranked their internal usage competitively on internal leaderboards, as previously reported by The Information. The Impact Analysis: Questioning AI's Productivity Value Uber's cutback raises a broader issue that the tech industry is currently facing: As enterprises pour money into AI, where exactly is the return on investment? Uber's COO, Andrew Macdonald, recently cast doubt on AI's productivity impact, noting during a podcast appearance that "it's very hard to draw a line" between AI usage and new consumer features. This sentiment reflects a growing skepticism in some quarters about the immediate practical benefits of AI investments. The Prediction: The Future of AI Spending in Tech AI ROI has so far remained a largely theoretical phenomenon that everybody hopes will eventually materialize. As more companies face similar budget challenges to Uber's, we may see a more measured approach to AI adoption across the tech industry. Companies will likely implement stricter usage tracking, set clearer ROI targets, and develop more sophisticated metrics to measure AI's actual impact on productivity and innovation before continuing to scale investments.

Introduction: Alphabet to Raise $80bn for AI Spending Alphabet, Google's parent company, has announced plans to raise up to $80bn in equity to fund its vast AI infrastructure investments. This move is one of the largest equity raisings ever and includes a $10bn share sale to investment giant Berkshire Hathaway. The AI Investment Strategy Alphabet, whose Gemini AI system has been growing its share of the AI chatbot market, says it will use the money to expand its “world-class AI compute infrastructure to meet its unprecedented customer demand.” The company stated: AI is driving an expansionary moment for Alphabet. The company is experiencing strong demand for its AI solutions and services from enterprises and consumers, at levels that are exceeding the company’s available supply. By scaling its investments, the company seeks to expand its foundational infrastructure to support the significant growth opportunity ahead. The Financial Implications However, such a huge fundraising also serves as a warning to the markets that, despite the many billions of dollars thrown at AI infrastructure, meaningful returns are limited. Jim Reid, market strategist at Deutsche Bank, noted: “Funding of the AI capex boom is becoming an increasingly key topic for markets.” The Berkshire Hathaway Partnership The decision to tap Berkshire Hathaway is eye-catching, given the company's history of providing crucial funding to companies in need. Under Warren Buffett, Berkshire made a habit of stepping in to provide important, and lucrative, funding for companies who really needed cash, such as the famous $5bn investment into Goldman Sachs at the height of the financial crisis. The Competitive Landscape Alphabet is also tapping investors before some of its largest AI rivals attempt to join the stock market. Yesterday, Anthropic, which makes the Claude chatbot, said it had filed confidentially for an initial public offering on the US stock market. Anthropic is now valued at $965bn after raising $65bn in funding, making it the world’s most valuable startup.

The Rise of AI Financial MarketsThe most important market of the future could be in LLM tokens — and financial groups are rushing to build new infrastructure for them. China's Shanghai Futures Exchange is currently designing a derivatives market for AI tokens, while major derivatives exchanges CME Group and the Intercontinental Exchange (the owner of the NYSE) have separately announced they're working on launching futures contracts for renting GPUs.Building the AI Derivatives InfrastructureGPU markets are still maturing, but given the wide range of companies using, selling, and renting GPUs, there's already a robust market for spot prices on GPU rental, typically charged by the hour. This has prompted major financial players to develop futures contracts that would allow businesses to hedge against fluctuating compute costs.Enterprise plans for major AI companies are commonly denominated in tokens: OpenAI, for example, charges $5 per million input tokens, and $30 per million output tokens if you want to use the API for its latest GPT-5.5 model. Even cloud providers are increasingly offering the opportunity to charge per token, as in Amazon's Bedrock system.The Economics of GPU and Token PricingAccording to data from AI Mining Co., which tracks daily GPU rental pricing across 28 marketplaces and cloud providers, median prices for Nvidia H100 GPUs ranged from $1.40 to $4.27 per hour across 13 marketplaces, while the average price for H200 GPUs were between $2.34 and $5 per hour across 10 marketplaces.Just over the past seven days, average H100 prices ranged from $2.79 to $3.33, showing the volatility that makes futures contracts attractive for risk management.Transforming the AI Investment LandscapeThe effort comes amid an unprecedented buildout of AI infrastructure. Cloud service providers, private equity firms, and infrastructure players alike have poured hundreds of billions into building data centers, anticipating that demand for GPUs and compute will continue to rise.An emerging crop of global neocloud companies is also vying for a piece of this demand. Some of these new entrants are specializing, focusing on inference, while others are competing with cloud giants like Oracle, AWS, and Google Cloud to offer their services to AI companies.The Future of AI Financial InstrumentsBy targeting AI tokens, the Shanghai exchange's derivative product would be tied to how AI companies price their services, giving businesses, investors, and data center operators a way to hedge against the cost of compute. As AI becomes increasingly central to business operations, these financial instruments will likely become essential components of the technology investment ecosystem.

The Lead: Singapore's Unexpected Economic Surge Singapore's economy has grown faster than expected in the first three months of 2026, with furious demand for AI chips outweighing the fallout from the US-Israel war on Iran. The city-state's gross domestic product (GDP) expanded 6 percent year-on-year in Q1, significantly beating the official advance estimate of 4.6 percent. Technical Breakthrough: AI-Driven Manufacturing Growth On a seasonally adjusted basis, GDP grew 1 percent from the previous quarter. The Trade Ministry attributed this growth to strong performances in Singapore's wholesale trade, manufacturing, and finance and insurance sectors. In particular, robust AI-related demand led to growth in the machinery, equipment & supplies segment of the wholesale trade sector, as well as the electronics and precision engineering clusters within the manufacturing sector, the ministry stated. Financial Impact: Global Context and Regional Position Singapore accounts for approximately 10 percent of global semiconductor production and 20 percent of semiconductor chip equipment production, making it a key player in the AI revolution. The United Nations recently cut its 2026 global growth forecast to 2.5 percent (down from 2.7 percent) due to the Middle East conflict. Despite these global challenges, Singapore maintained its 2026 growth outlook at between 2 and 4 percent, acknowledging downside risks from rising energy and fertilizer prices amid the closure of the Strait of Hormuz to most shipping. Industry Transformation: The AI Boom and Singapore's Strategic Position As one of the world's most trade-reliant economies, Singapore has played a major role in the global rollout of AI technologies. The city-state's specialized manufacturing sector has benefited significantly from the ongoing AI investment boom. The AI-related investment boom is powering the manufacturing sector, and unless the Singapore economy runs out of oil, strong activity in manufacturing will continue to drive growth, said Khoon Goh, head of Asia research for ANZ. Future Outlook: Balancing Growth with Global Uncertainties Economists predict that the full impact of the Middle East crisis may become more apparent in Q2 2026, though the strong Q1 performance provides a solid foundation for the rest of the year. Local economists expect around 3.6 percent growth for 2026, acknowledging significant downside risks. The 6 percent year-on-year figure is strong, especially for a mature economy like Singapore, noted Yeow Hwee Chua, an economics professor at Nanyang Technological University. It is certainly encouraging, although I would interpret it with some caution given Singapore's high exposure to global demand and external conditions.

Elon Musk saw his lawsuit against OpenAI founders and Microsoft thrown out after a swift jury decision, underscoring the weakness of his claims and the timing of his filing. Jury Rejects Musk’s Claim of Charitable Trust Breach The jury concluded that Musk’s allegations—centered on a purported "breach of charitable trust" and "unjust enrichment"—were unsubstantiated. OpenAI’s attorneys systematically dismantled the case, while Musk’s team focused on questioning Sam Altman’s credibility. After the verdict, Musk briefly posted a deleted comment accusing Judge Yvonne Gonzalez Rogers of activism. Numbers, Dates, and Key Facts from the Trial 2017: Musk asked Greg Brockman to send OpenAI researchers to Tesla for autopilot assistance. 10,000 images: The number of corner‑case images cited by Ilya Sutskever that could improve Tesla’s self‑driving software. Aug. 5, 2021: Legal deadline the jury considered for Musk’s knowledge of OpenAI’s for‑profit activities. Statute of limitations: The court emphasized that Musk’s delayed filing undermined his claim. Broader Impact on AI Non‑Profit Governance and Founder Disputes The case spotlights the growing tension between nonprofit AI research missions and commercial off‑shoots. Legal scholars, such as Dorothy Lund, note that using charitable donations to staff a for‑profit venture could breach fiduciary duties. The verdict may deter future lawsuits that attempt to retroactively police the allocation of nonprofit resources, especially in fast‑moving tech sectors. Future Outlook for Musk, OpenAI, and Legal Strategies With the lawsuit dismissed, Musk is likely to focus on other avenues—potentially leveraging his family office, Excession, for future AI investments. OpenAI, bolstered by the win, may continue expanding its for‑profit arm without heightened legal scrutiny, though board oversight could tighten. Industry observers expect more explicit governance clauses in AI nonprofit charters to pre‑empt similar disputes.