U.S. semiconductor manufacturer GlobalFoundries is reportedly weighing a merger with Taiwan-based United Microelectronics.

U.S. shares of United Microelectronics popped 13% on the news, while GlobalFoundries shares dipped about 1%. Nikkei reported the news, citing sources familiar with the deal.

The merger would create a company based in the U.S with production capabilities in Asia, the U.S. and Europe, according to the report. The combined entity would aim to secure American access to mature chips amid potential risks from China competition and tensions between China and Taiwan, Nikkei reported.

The new company would eventually invest in research and development in the U.S. and potentially become an alternative to Taiwan Semiconductor Manufacturing, the report said. Taiwan Semiconductor announced a $100 billion investment in the U.S. earlier this month to bolster chip manufacturing. The deal brought the company’s total investment in the U.S. to $165 billion.

Taiwan has become a hub for global chip manufacturing, building chips for some of the largest companies such Nvidia and Apple. Taiwan Semiconductor is by far the leading worldwide supplier.

Both GlobalFoundries and United Microelectronics have reportedly discussed the merger and informed government officials from both countries. United Microelectronic had previously looked into buying or building production plants in the U.S. but ditched the possibility due to costs, Nikkei reported.

Read the full report here.

Amazon on Monday released a new AI model that can take actions in a web browser on a user’s behalf, a move that puts it in more direct competition with OpenAI, Anthropic and other companies that have developed the so-called “agents.”

The new model, called Nova Act, is designed to help developers build agents, or AI software that can complete multi-step tasks for users without supervision. Amazon showed Nova Act searching for “apartments by biking distance to the train station” as one example of a task it can complete.

A growing number of companies are building AI agents as they look beyond text and image generators.

Anthropic, the Amazon-backed AI startup founded by ex-OpenAI research executives, released its Computer Use tool in October. The startup said the tool can interpret what’s on a computer screen, select buttons, enter text, navigate websites and execute tasks through any software and real-time internet browsing.

In January, OpenAI released a similar feature called Operator that will automate tasks such as planning vacations, filling out forms, making restaurant reservations and ordering groceries. The Microsoft-backed startup described Operator as “an agent that can go to the web to perform tasks for you.”

OpenAI followed up that release in February with another tool called Deep Research, which allows an AI agent to compile complex research reports and analyze questions and topics of the user’s choice. 

Google launched a similar tool of the same name last December, which acts as a “research assistant, exploring complex topics and compiling reports on your behalf.”

Nova Act is initially launching in research preview for developers, Amazon said. The company is also launching a website that lets users experiment with its Nova AI models.

The release is part of a broader strategy within Amazon to invest heavily in generative AI software. Amazon has introduced a flurry of AI products, including its own set of Nova models, Trainium chips, shopping and health assistants, as well as a marketplace for third-party models called Bedrock. It’s also overhauling Alexa, the digital assistant it launched more than a decade ago, with AI capabilities.

Earlier this month, Amazon’s cloud unit said it’s forming a group dedicated to developing agentic AI that’s being led by longtime Amazon Web Services executive Swami Sivasubramanian. It’s also created an internal team focused on building artificial general intelligence, or AGI, which broadly refers to AI that is as smart or smarter than humans. The team reports directly to Amazon CEO Andy Jassy.

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Value within the artificial intelligence industry is slowly shifting, from the companies developing models to the apps building on top of them. 

Early in the AI race, critics viewed apps like Perplexity, Replit, Sesame and Abridge as second-rate middlemen, slapping an interface on someone else’s technology. They were disparagingly known as AI wrappers: companies with entire apps or businesses wrapped around existing models. Companies like OpenAI, Google, Meta and Anthropic developed their own models.

The arrival of ultra-efficient models and increasing model commoditization accelerated the shift.

“There was an impression that the only way to compete in AI would be to raise hundreds of millions of dollars to pre-train these web-scale models that could solve every problem underneath the sun, and that was the only game in town for AI,” said Shiv Rao, founder and CEO of the healthcare AI startup Abridge. “Very quickly, people figured out that actually, value moves up the stack.” 

Megacaps like Microsoft poured billions into the first stage of the AI arms race, focusing on the infrastructure and model layer. But models are now increasingly looking commoditized, narrowing the advantage that any model-builder had. While they focused on delivering raw capability and intelligence, app companies looked at real-world uses and solutions.

“[Wrapper] just sort of means that it feels less thoughtful. It feels like you’re giving this little package around what was built. As opposed to what it really means is, ‘I’m going to understand the customer’s problem,’ ” said Andreessen Horowitz partner Bryan Kim. “I’m going to marry this and deliver a solution to what you’re trying to achieve.”

Wrappers have even changed the way Silicon Valley builds, ushering in the era of vibe-coding. With an app like Cursor, one of the fastest-growing startups ever, anyone can develop an app without a degree or years of coding expertise.

“I love the phrase vibe-coding because, actually, I think it points to … this new way that we’re going to interact with these systems where we’re not necessarily going to interrogate all of what they do in process,” said E14 Fund Managing Partner Calvin Chin. “Over time as the models improve and these products built on top of them improve, we’re going to get other kinds of vibe-activities in the economy. So maybe it’s vibe-lawyering, vibe-accounting, and we’re going to trust the models more and more.”

Watch the video to learn more.