• Google’s delayed 3.5 Pro model has competitors taking jabs.
• One analyst said the delay has “shifted perception from leading edge to trailing edge.”
• “Gemini who?” wrote Meta’s chief AI officer, Alexandr Wang, on X.

In the AI race, the throne is never safe. Just ask Google.

After the success of Gemini 3, Google found itself in a strong position at the end of 2025. As of this week, the situation is a little shakier.

While the company just rolled out three faster, more cost-effective models, it continues to delay its next frontier model, Gemini 3.5 Pro, and it’s unclear whether this week’s launches will be enough to keep users and investors happy in the interim.

Some of Google’s competitors are using the opportunity to land a few jabs.

Alexandr Wang, Meta’s chief AI officer, wrote on X “gemini who?” in response to a leaderboard that ranked Meta’s Spark model above one launched by Google this week.

Thibault Sottiaux, a member of technical staff at OpenAI, also took an apparent jab at the search giant. In a post on X, Google’s Logan Kilpatrick announced that pre-training on Gemini 4 — the next big milestone model — had begun. “Hope it finishes one day too!” Sottiaux replied.

Google declined to comment.

‘Too early to count anyone out’

Google’s delay is particularly glaring because OpenAI and Anthropic have rolled out new top-tier models in recent weeks. The pushback of Gemini 3.5 Pro has “shifted perception from leading edge to trailing edge,” said Josh Beck, an analyst at Raymond James, in a note this week. He said he saw this as a byproduct of the fast pace of change among the labs right now.

At the same time, Google’s business has been humming along nicely in recent quarters, with strong momentum across Search, YouTube, Cloud, and other areas benefiting from Google’s AI advancements. Google is also betting that faster, more cost-effective models may be a winning strategy at a time when token costs are racking up.

Google’s focus on more efficient models has received praise from some users.

“Google gets a lot of criticism on here for falling behind on agentic coding, but Gemini 3.5 Flash has long been my daily driver for agentic document extraction, which is one of the highest-value use-cases for LLMs IMO,” Kyle Walker, founder of Clearfork Intelligence, wrote on X.

Still, Google may need to address this trade-off between efficiency and power when it announces Q2 earnings on Wednesday evening. Analysts are likely to raise the topic of 3.5 Pro and its release timeline.

“I love Gemini, probably more than I should but them hyping 4 before even delivering 3.5 Pro is a lil weird,” Anshel Sag, analyst at Moor Insights & Strategy, wrote on X.

Sag told Business Insider he felt that Google hyping up Gemini 4 was an “admission they already have something better.” However, he said the “feverish pace” of AI right now doesn’t necessarily yield meaningful improvements.

“I just feel like Google is a much bigger company and moves a bit differently from its competitors,” said Sag.

He added: “It’s just way too early to count anyone out.”

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• Summer Farmen, a mom of three, was diagnosed with a rare form of lung cancer despite never smoking.
• The condition, known as alk-positive lung cancer, inspired her to become an advocate to give back.
• Farmen is celebrating six years as a survivor thanks to targeted therapy medications that fight tumors.

When Summer Farmen first noticed the shortness of breath and persistent tiredness, she didn’t think much of it.

It was early 2020, but COVID wasn’t her first thought, since she otherwise felt fine.

Within a month, she found herself choking and coughing during casual conversations.

The Pennsylvania-based mom of three was used to taking extra care of herself, since she and her husband are primary caregivers for their son with cerebral palsy.

“I always made sure I was eating healthy and staying in shape,” she told Business Insider. “So here I am, 44 years old with, I thought, no risk factors for cancer, but we’re mid-pandemic, and I suddenly was struggling to breathe, gasping for breath, coughing incessantly.”

As the weeks went by, Farmen felt worse and worse. When the family’s routine Fortnite gaming sessions left her exhausted, she wondered if it could be asthma, pneumonia, or coronavirus after all.

After antibiotics and other treatments didn’t help, she went to the emergency room, fighting for air, where doctors drained 2 liters of fluid from her lungs.

“I joke that it was a Diet Coke bottle that had been just compressing my lung,” Farmen said.

She was eventually diagnosed with stage four lung cancer, related to an unusual type of gene abnormality.

A typical patient in her situation might have six months to live, maybe a year and a half with good luck. More than six years later, at age 50, Farmen is not just surviving but thriving. She used her experiences as a patient to advocate for more and better research to help others facing the disease.

“It’s so therapeutic to give back,” she said. “We’re educating and empowering patients that you’re not just riding along for this, you’re in the driver’s seat. Make your voice heard.”

A rare genetic mutation

After ending up in the ER, the last thing Farmen expected was to celebrate a lung cancer diagnosis. But that’s exactly what happened.

Initially, doctors feared her cancer had spread from another organ, such as her uterus, and could be terminal. An end-stage diagnosis would mean the only treatment options would be to keep Farmen comfortable through her final days.

While lung cancer is one of the deadliest cancers, Farmen was diagnosed alk-positive, a specific subtype that’s highly treatable.

“I got the call that it was lung cancer, and my dad and I are in the front yard hugging and crying. We’re so happy,” she said.

Her specific form of cancer is caused by a gene mutation that occurs during the patient’s lifetime, so it can’t be passed down to children.

It responds well to targeted therapy, a precision cancer treatment that blocks the cancer’s fuel sources, such as proteins, to prevent tumors from growing.

Farmen’s treatment plan included medications called tyrosine kinase inhibitors that work by interrupting signals that tell cancer cells to grow and divide uncontrollably.

While Farmen said she’s generally an optimist, the treatment process “wasn’t all sunshine.” She was afraid of never teaching her son to drive or missing her daughter’s high school graduation.

“I went to dark places. I was in the fetal position several times, but I’d never let myself stay there,” she said.

A major turning point as she underwent treatment was finding support groups with other alk-positive patients.

“It was a lifeline immediately. You’re finding out about different patient experiences. You’re getting validation,” Farmen said. “Right away in the beginning, I’m learning about strength and adversity, the importance of patient preferences, the importance of a patient voice.”

From patient to advocate

Farmen’s journey into the alk-positive cancer support community started with an art therapy class on Zoom. Before long, she was helping to expand the program and organizing educational sessions.

“Soon after I became involved, I knew I had to give back. I had to help others,” she said.

The nonprofit behind the programs, Alk Positive Inc., funds cancer research to improve patients’ quality of life while providing resources such as support groups and clinical trial information.

Farmen is now the organization’s vice president and a contributor to a recent study published in the journal Lung Cancer.

The research focused on patient and caregiver preferences in balancing the potential benefits and side effects of treatment options, a key issue in the increasingly personalized world of cancer care.

Farmen said that as a cancer survivor, giving back has helped her come to terms with some of the psychological toll. The physical and emotional strain is ongoing.

“You wouldn’t pick me out of a group as a stage four lung cancer patient, but there are debilitating side effects that everybody experiences differently from these life-extending treatments that we’re on,” she said. “I still have a stage four cancer diagnosis. I still have scans every three months. It’s not if my cancer progresses, it’s when my cancer progresses.

For now, Farmen, who turned 50 in April, is busy celebrating five decades of being alive. “I’m so lucky to be 50. I’m so happy to be here. Growing old is a privilege,” she said.

• Zhipu’s open-weight AI model GLM 5.2 wow developers, but its stock has plunged.
• Open-source software benefits from easy, cheap distribution. Open-weight AI is very different.
• Other companies often run Chinese open-weight models. That’s where the money is made.

The angst over China’s latest AI models is missing an important business fact: “open weight” AI is not the same thing as open-source software.

Open-source software, where the code is freely shared, can be an amazing business. Think Red Hat, which IBM bought for $34 billion. Open-weight AI models are different — and, so far, they’re proving to be a terrible business.

Take Z.ai, also known as Zhipu. It’s publicly traded, so we can see its finances. Last year, the Chinese company lost almost $500 million on revenue of about $107 million.

Zhipu is the lab behind GLM 5.2, an open-weight AI model that wowed the industry when it launched last month. You might expect the stock to have soared. Instead, Zhipu shares have plunged more than 40% over the past month.

MiniMax, one of the only other independent Chinese AI labs that’s publicly traded, lost $250 million last year on revenue of just $79 million. Its shares have fallen more than 50% in the past month.

“Open-weight models have a challenging path to making a profit,” William Blair analyst Arjun Bhatia wrote in a recent note to investors, in the understatement of the year.

Open-weight AI isn’t open-source software

The key difference comes down to economics.

Software can be distributed almost for free. Once it’s written, sending another customer a copy costs practically nothing. Profit margins improve as software companies grow.

AI doesn’t work that way. Every answer requires expensive chips, electricity, and data-center capacity. The next unit of software is nearly free; the next unit of intelligence is not.

Moonshot AI, another Chinese lab, illustrated the problem last week. Its new Kimi K3 open-weight model impressed the industry with frontier-level performance. But days after launch, the company had to halt new customer sign-ups because it didn’t have enough computing power to run the model.

If Moonshot were selling traditional software, adding millions of users would be relatively easy. Instead, every new customer increases the company’s infrastructure bill, capping its growth.

Someone else captures the profits

The way open-weight AI models are run, a process known as inference, makes the business situation worse.

Open-weight AI labs give outsiders their models’ trained numerical parameters, allowing them to download and run them. (Parameters are like tiny numerical dials inside a model’s brain that determine how these systems learn from data and what outputs they produce).

After that, these models are usually run by other companies, such as cloud giants Amazon, Microsoft, Google, Oracle, and Alibaba. There are also specialist providers such as Fireworks AI and Baseten, although they largely rent capacity from the big cloud companies.

Companies can also download these open weights and run the models themselves. Or, they can also use the Chinese model maker’s own inference service, but in the Western world, most corporate customers don’t do that for data security reasons.

Only that last option reliably generates real revenue for the model creator. In the other three cases, the AI lab that spent hundreds of millions of dollars building the model may receive little or no ongoing revenue.

That leaves the model makers in a difficult position. They’ve paid heavily to train the systems, then given away the key assets.

No wonder Alibaba’s stock is up about 13% over the past month, while AI labs Zhipu and MiniMax have been crushed.

Not Red Hat

“Unlike open-source software, open-weight models do not generate significant sums of revenue by selling support, services, and enterprise editions around the free offering (the Red Hat playbook),” William Blair’s Bhatia wrote.

“Instead, they primarily generate revenue by hosting the model and selling inference compute. But inference workloads will flow to whoever can operate the inference infrastructure most efficiently, and this is usually not the model provider,” the analyst added.

Raimo Lenshow, an analyst at Barclays, recently came back from China after researching the country’s AI sector. He reached a similar conclusion.

“Intense domestic competition has also led to more aggressive pricing competition,” the analyst told investors. “Some major models remain open-source or open-weight, accelerating the pricing pressure throughout the system. While this helps drive faster commercialization, it is also adding uncertainty to long-term profitability for those AI labs.”

So why give the models away?

Open technology has long been a strategy for challengers trying to catch market leaders. A late starter may not be able to match a leader’s customers or distribution, but it can spread its technology widely, attract developers, and make the leader’s product harder to sell at premium prices.

That may be exactly what China and its AI labs are trying to do. Open-weight models put pressure on OpenAI, Anthropic, and other US leaders by offering capable alternatives at lower prices. Even if the Chinese labs make little money themselves, they can force American competitors to cut prices and make it harder to recover the billions they spend training new models.

Bhatia said Chinese labs may be releasing open-weight models with “little regard for near-term profitability.” In his view, openness can turn advanced AI into a commodity, weakening the business model of US companies that keep their technology closed.

The financial payoff for the Chinese labs may come much later — or may be less important than the broader strategic benefit to China.

China’s leadership is now openly encouraging that strategy. In a recent speech in Shanghai, President Xi Jinping said countries should seize the opportunity to encourage “open-source, openness, collaboration, and sharing.”

A statement like that is more than a casual policy suggestion. Chinese technology companies are expected to align with the government’s strategic priorities.

After Xi put openness at the center of China’s AI strategy, companies such as Moonshot, Zhipu, and MiniMax are likely to face strong pressure to follow that direction — even if it makes their own path to profit much harder.

Sign up for BI’s Tech Memo newsletter here. Reach out to me via email at abarr@businessinsider.com.

• Curative’s CEO said the company canceled an annual $600,000 Salesforce bill.
• He said his company replaced the CRM with a tool that AI helped build in two months.
• He’s describing the SaaSpocalypse thesis: that AI coding tools will challenge software companies.

Curative CEO and founder Fred Turner believes in the SaaSpocalypse.

During an interview on the “20VC with Harry Stebbings” podcast, the health insurance executive was asked whether he bought the theory that software-as-a-service was dying.

“Yes,” Turner said, bluntly.

When asked why, he said, “I see the number of contracts that we’re canceling. We just recently canceled our Salesforce contract because we have an internal CRM that was vibecoded.”

That Salesforce contract cost Curative $600,000 a year, Turner said. He also said that Curative built its replacement in two months.

Overall, Curative plans to cut about 80% of its SaaS spending this year, according to Turner. The company is spending on AI instead, he said.

A Curative spokesperson told Business Insider that the startup had made a “notification of cancellation” for its Salesforce CRM contract.

“As Fred said publicly, Curative terminated its Salesforce CRM contract,” a Curative spokesperson said. “We do still use Slack,” the spokesperson said. Salesforce purchased Slack in late 2020 for $27.7 billion.

A Salesforce spokesperson told Business Insider that 150,000 companies still use its platforms and highlighted that its tools are built to navigate complex healthcare patient regulations, such as HIPAA.

“Our platform is built with trust and governance at its core,” a Salesforce spokesperson told Business Insider.

Salesforce’s CEO has pushed back on SaaSpocalypse fears

Turner is describing the exact SaaSpocalypse fear that spooked Wall Street at the start of 2026.

As AI coding agents quickly improved, investors feared that companies that bought software-as-a-service would turn to AI tools and build their own bespoke products. Software providers — such as Salesforce, Asana, DocuSign, ServiceNow, Adobe, and Workday — saw their stocks drop by 20% to 50% amid those snowballing concerns.

Salesforce’s CEO, Marc Benioff, has also strongly pushed back, saying that he’s still seeing “incredible demand” for his products. He’s also pointed out that Anthropic, the massive AI lab behind Claude, still uses Salesforce services.

“If there is a ‘SaaSpocalypse,’ it may be eaten by the ‘SaaS-quatch’ because there are a lot of companies using a lot of SaaS because it just got better with agents,” Benioff said during a February earnings call.

Turner acknowledged that replacing outside software with custom-built systems hasn’t been perfect. Maintenance is “definitely one of the most challenging pieces,” he said.

He also said Curative’s spending on Anthropic had surged as the company found more uses for AI.

“Our Anthropic cost over the last six or seven months has 6x’d every month, from a base of a couple of tens of thousands of dollars, now up to millions of dollars a month,” Turner said. “Eventually, we’re going to have to stop that spending increase because it’ll get unreasonable, but we just keep finding new things to do with it.”

For Curative, however, Turner said the economics would still work — even if Anthropic were to quintuple its prices.

He pointed to Gwen, a bespoke AI agent Curative uses to negotiate contracts with doctors and other healthcare providers. Turner said completing one contract before AI had cost the company an average of $1,500 to $2,000. Gwen’s average cost is about $70, he said.

“What we’ve done is said, ‘Well, now that we have the agent, we can do 10 times as many contracts this year as we could do last year,'” Turner said. “So, we’re going to do 10 times, and then we’re going to try and do 20 times, and we would just do a lot more volume than you could possibly have done with a human team.”

• Mike Recupero is the first VP of finance for Amazon’s Leo satellite business.
• Amazon is putting together a seasoned leadership team for Leo.
• Amazon expects Leo to generate meaningful growth and returns.

Amazon’s Leo satellite business has appointed its first dedicated finance VP, another sign the company is building the satellite venture into a more independent business.

Mike Recupero, who most recently served as Alexa’s finance chief, was named Leo’s VP of finance earlier this month, according to people familiar with the move. The newly created role makes him the first VP solely overseeing Leo’s finances.

Previously, Recupero spent about a year as GameStop’s CFO after serving as finance chief for several Amazon businesses, including Prime Video and North America retail.

Until now, Leo’s finances were overseen by executives who also managed Alexa, supported by more junior finance leaders.

The appointment reflects how Amazon is assembling a seasoned leadership team around Leo, formerly known as Project Kuiper.

Over the past two years, Leo has also recruited former GitLab chief revenue officer Chris Weber as vice president of sales and marketing and former T-Mobile executive Clint Patterson as chief marketing officer. VP of technology Rajeev Badyal leads the overall Leo business and reports to Panos Panay, SVP of devices, Alexa, and Leo.

Recupero will primarily oversee Leo’s multibillion-dollar infrastructure buildout, including satellite manufacturing and launches, as well as the integration of Globalstar, the satellite communications company Amazon is acquiring for $11.6 billion, the people said.

Amit Singh has replaced Recupero as Alexa’s finance lead.

Leo is one of Amazon’s biggest long-term bets beyond its core retail and cloud businesses. CEO Andy Jassy previously said Leo already had a series of revenue commitments from enterprise and government customers and is expected to generate meaningful growth and returns for Amazon. The company said earlier this month that Leo has completed 14 missions and launched 396 satellites so far, making it the third-largest satellite constellation in orbit.

Wall Street is also growing more bullish on the business. Bank of America recently estimated Leo could generate $20 billion to $25 billion in annual revenue by 2032 and eventually be worth $200 billion to $275 billion.

The growing enthusiasm has not eliminated the risks. A Blue Origin rocket that Amazon plans to use for future Leo missions exploded during a ground test in June. Leo’s VP Badyal sought to reassure employees at the time, saying such setbacks are an expected part of spaceflight and that the company would continue pressing ahead.

Amazon declined to comment.

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• Corner, a social mapping startup that helps people find local spots, has doubled its funding.
• The New York-based startup has raised $7.5 million, the company confirmed.
• It’s one of many new social media startups trying to break through.

Finding a really good restaurant or bar takes effort.

Corner, a startup looking to make that process easier, has raised more capital to stake its claim in the map game.

Corner, which was founded in 2022, is a social-mapping app targeting Gen Z users who want to meet up in real life. In the app, users can leave reviews, share photos, and curate lists. Locations are added to Corner’s map only when a user saves it.

The platform has more than 250,000 users — primarily in New York and Europe — across 425 cities, the company said.

The startup has nearly doubled its total funding since 2025.

In September, Corner told Business Insider that it had raised $3.75 million across two rounds from VC funds including Abstract Ventures, Tapestry, and 1517. The startup also has angel investors, like Partiful’s cofounder Shreya Murthy.

The New York-based startup has raised new funding since, with total funding reaching $7.5 million, Corner confirmed. The startup is gearing up to raise a Series A round.

Corner isn’t the only app trying to make waves in the social-mapping and restaurant-saving categories.

Beli, a rival app for saving and sharing restaurants, had raised $12 million in venture capital as of June 2025, the company previously told Business Insider. Apps like Amo’s Bump, a social app for tracking your friends, are also gaining steam. Meanwhile, Corner has to compete with larger players like Google Maps, Apple Maps, and Yelp.

Corner has carved out a following on social media as it grows its platform and business. Its digital magazine has over 91,000 followers on Instagram. Eliza Wu and Jake Xia, Corner’s cofounders, have also become faces of the brand on social.

A map with personalized recommendations

Last year, Corner rolled out an overhauled search feature that leverages AI to suggest recommendations based on Corner reviews and content.

“Our proprietary dataset powers true personalization instead of virality-based recommendations,” said Corner CEO Wu.

Corner’s been experimenting with new features, too.

Recently, I’ve noticed Corner will let me know when a reservation opens up at a restaurant I’ve saved. The app also now lets you add bookings and events, provides a round-up of places that people — including your friends — are raving about, and offers age- and location-based suggestions on where to go out.

“Of everything else that I’ve seen, and I’ve seen this idea tried a dozen times in the last 10 years, this was the best execution I’d seen,” Abstract Ventures’ Ramtin Naimi, a Corner investor, told Business Insider in September.