Sustainabl Agent Surface
All articles published in English, by date, category and author.
1347 articles · Page 9 of 57
Simon Song was 29 years old when he closed a $200 million round and crossed the billion-dollar valuation threshold. VAST, his AI model startup for three-dimensional content, has just become a unicorn. The announcement comes just three months after the company closed its Series A with $50 million led by Alibaba and Hengxu Capital.
There are industries that don't die all at once. They erode. They cede ground little by little, first at the margins, then at the center, until one day the last player closes and everyone nods as if it had been inevitable. That is what happened to independent bookstores in the United States during the first decade of the century. And it was precisely at that moment, when the narrative of collapse seemed sealed, that Ann Patchett opened Parnassus Books in Nashville.
There is a gap between what executives say they believe about artificial intelligence and what their organizations actually do with it. It is not a knowledge gap. It is a strategic attention gap, and it carries a cost that few boards of directors have honestly quantified.
On the first day of June 2026, the US stock market delivered an image worth more than any macro report: while Intel fell 4.05% and Texas Instruments lost 4.73%, Nvidia rose 4.87% and Micron Technology surged 5.90%. On the same day, Exxon Mobil gained 2.64% and Chevron 2.68%, with a consistency the tech sector could not replicate. Technology fragmented. Energy advanced as a block.
Three quarters of venture capital firms already use artificial intelligence to evaluate investment opportunities. That figure alone sounds like inevitable modernisation. But there is a structural tension that percentage fails to capture: language models are extraordinarily good at doing exactly what venture capital cannot afford to do too often, which is looking backwards.
When Thapanee Techajareonvikul took over as President and CEO of Berli Jucker in 2023, she did not inherit a vacant position. She inherited a 142-year-old company, a family power structure that distributes control among five siblings, and the implicit expectation that nothing changes too quickly. That tension — between the inertia of a legacy and the need to stamp it with her own direction — is exactly what makes this case worth examining beyond the celebratory profile.
Three quarters of the venture capital raised in the last year went to just five companies. Not five sectors. Not five categories. Five companies. That figure, stated bluntly by Niko Bonatsos of Verdict Capital at a recent TechCrunch panel in Athens, captures more precisely than any market report what is happening in global venture capital: an unprecedented concentration that coexists, paradoxically, with a narrative of distributed innovation and open opportunity.
There is a type of stock market discount that deserves attention and another that deserves caution. The difference lies in the origin of the decline. When a stock loses a quarter of its value while revenues rise, the market is not reading the destruction of a business: it is punishing the loss of profitability on every dollar sold.
There is a moment in the evolution of any technology market when competitors stop differentiating themselves by what their products do and start differentiating themselves by how their customers control them. IBM reached that moment with clarity at its Think 2026 conference in Boston, where it presented what it calls an agentic operating model built on four pillars: agents, data, automation, and hybrid sovereignty. The last of those pillars, and the most strategically loaded, is IBM Sovereign Core, a governance platform that operates at the execution infrastructure level, not as an application configuration layer.
Unmanned Underwater Vehicles and the Adoption Problem AUKUS Didn't Name On May 30, 2026, on the sidelines of the Shangri-La Dialogue in Singapore, the defense secretaries of the United States and the United Kingdom shared an unusual moment of institutional self-criticism.
The official picture of corporate AI adoption looks tidy: approved investments, pilot projects underway, dashboards full of productivity metrics. But there is a layer those reports never capture, and that is precisely where real risk accumulates. Gartner's Hype Cycle currently places generative AI in the 'Trough of Disillusionment', the third of five stages where expectations begin to be measured against concrete results.
There is a moment when a company stops managing its transition and starts managing its fear. The acquisition of Stack AI for $75 million, announced on May 29, 2026, arrives right at that threshold. Asana has lost approximately half its market value since the AI boom began.
In November 2021, in Glasgow, G7 governments and the European Union unveiled what they described as a new architecture for climate finance: the Just Energy Transition Partnerships. The idea was ambitious in its design. Four years later, the balance sheet is uncomfortable: funds have not flowed at the promised pace, and in March 2026 the United States government formally withdrew its participation, pulling more than $3 billion in commitments linked to Vietnam and Indonesia.
The stock market forgave Ola Electric in a matter of weeks. From its all-time low of 22.25 rupees per share, recorded in March 2026, the Indian electric scooter manufacturer accumulated a 93% recovery in just two months, reaching 42.88 rupees on the National Stock Exchange of India by late May. But there is an inconvenient gap that no stock market rebound can hide: Ola Electric's all-time high was 157.40 rupees per share.
There are corporate decisions that sound like efficiency moves but are really bets. The one Marc Benioff just articulated on Salesforce's fiscal Q1 2027 earnings call falls into that category. The CEO of the $145 billion cloud platform was explicit: the company is not hiring more engineers, it is not expanding general and administrative functions, and the only area where the org chart is growing is sales.
There is a specific moment in Andre Rebelo's trajectory that deserves more attention than the launch of his Fortnite skin. It's not the day Epic Games added him to the Icon Series. It's the moment before, when Rebelo stopped asking himself what content he could produce and started asking what he could build.
There is one piece of data in this story that deserves pause before we talk about funding rounds or language models: according to the CEO of Orbital Industries, developing a new cooling fluid for data centers would normally take ten years and one hundred million dollars. The company says it did it in months, at a fraction of that cost. If that claim holds up under validation from major chip manufacturers, this is no mere laboratory achievement.
Starting July 4, 2026, the U.S. Small Business Administration (SBA) doubles the combined guaranteed financing limit a single borrower can receive: from $5 million to $10 million. It's the highest cap in the agency's history. And while the news may seem like a simple ceiling adjustment, what lies beneath the surface is something more uncomfortable for many small business owners: a line that separates those who can grow through the federal financing system from those who simply aren't in that game.
There is a pattern that repeats itself frequently enough to deserve attention: an organisation announces a digital transformation, allocates budget, hires consultants, implements platforms and, two years later, discovers that almost nothing changed where it mattered. Processes are still slow. Frontline teams did not adopt the tools. And leadership, which managed everything from control dashboards, cannot precisely explain what went wrong.
There comes a moment in the life of every digital platform when the game changes completely. You stop obsessing over how many users you have and start asking how much money you can extract from the ones already there. Spotify just announced it has reached that moment, and Bank of America is cheering from the front row.
More than $1.5 trillion in enterprise software valuations evaporated over the last two years. Not for lack of investment in artificial intelligence, but because the investment landed in the wrong place. This is the paradox that defines the current moment: companies have never spent so much on AI and, at the same time, it has never been so hard to show where the value actually is.
Hugging Face has just published the blueprints, wiring, and software to build a pair of humanoid legs for approximately $2,500 in parts. No arms, no torso, no head. Just bipedal 3D-printed legs assembled with off-the-shelf components. The question this opens is not technical. It is structural: when an AI platform decides to lower the entry cost of robotic hardware to the price of a mid-range laptop, it is moving a piece on the board that does not move out of mere generosity.
There is a widespread way of getting AI wrong in business. It consists of measuring the maturity of a system by how many jobs it managed to eliminate. That metric doesn't measure maturity: it measures speed without governance, which is exactly the condition that precedes the most costly collapses in critical systems.
There is one figure that explains almost everything: €585,000 collected in the first business, valued at €900,000, without a single client meeting and without hiring anyone. The second business followed the same pattern. By 2022, its valuation reached €560,000 with €90,000 raised.