Evening tech roundup: models, chips, and dev leverage

Meta is launching the first AI image generation model made by its Superintelligence Labs division. The Muse Image model now powers the image-making tools across the Meta AI app, Instagram, and WhatsApp, and it’s coming soon to Facebook and Messenger, according to an announcement on Tuesday .

It’s part of the growing Muse family of AI models that replace Meta’s Llama lineup. Alexandr Wang, who Meta hired to head up its Superintelligence Labs last year, says on Threads that Muse Image is “agentic,” meaning it works with its Muse Spark large language model “to reason through your prompt, search the web, and plan before it generates.”

Next 1 / 4 Image: Meta As noted by Meta, users can @ mention other Instagram accounts in Muse Image prompts, allowing the AI model to incorporate their likeness into its output. Meta says “tagging a username lets Meta AI use public photos to build a visual,” but notes that users can control how people reuse their content for AI.

Users can also transform images using suggested prompts and create designs for things like invitations and postcards. Additionally, Muse Image can redesign rooms based on an image pulled from Facebook Marketplace (or elsewhere on the web), and allows users to make changes directly to photos by drawing right on top of them, which they can then share to their feed, story, or chat.

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A report says SpaceXAI and Cursor are preparing to launch their first jointly built AI model.

The launch was pushed back, and the stated reason is efficiency improvements before public release.

The story centers on timing and model quality tradeoffs rather than a finished feature set.

This is significant for teams evaluating model choices in coding workflows and agent stacks.

DeepSeek, the Chinese startup developing large language models that are competitive with those from US companies like OpenAI and Anthropic, is planning to enter the silicon business, according to Reuters .

Citing three people familiar with the matter, Reuters writes that DeepSeek has been working on a move into silicon for about a year. It has been meeting with potential partners in the hardware and silicon space and has been hiring engineers for the project.

The focus is on data center chips for inference, not training, and the goal is likely to reduce reliance on both Huawei and Nvidia.

Nvidia is the chipmaker for most AI companies in North America and Europe, but a United States export ban has prevented the company from achieving a similar presence in China. Huawei controls about half of the data center chip market there, and DeepSeek isn’t the only one trying to enter; Chinese tech giants like Alibaba and Baidu have been making moves, too.

While chip export controls in the US are a major reason this is an urgent concern for DeepSeek, US-based AI companies are making similar chip plans.

As AI costs continue to rise , companies are looking for ways to cut back. The most recent example is Microsoft, which has reportedly begun to deploy a cost-savings strategy by relying less on software from OpenAI and Anthropic and instead deploying its own in-house models.

While Microsoft still relies on those third-party models, it has also increasingly sought to stand up its own AI agents. Last month, at its annual Build conference, the company announced the launch of seven new MAI models , including an agentic coder and a text-to-image generator.

When reached for comment by TechCrunch, Microsoft said that it had nothing further to share.

Microsoft’s apparent cutbacks are part of a broader trend. After a brief blitz of “tokenmaxxing” earlier this year, the last few months have seen a news cycle awash in stories about tech companies acting significantly more thrifty. Other large companies — like Amazon , Uber , Meta , and Accenture — have also reportedly made moves to curb spending.

The immense cost of providing and buying AI services has become a controversial part of the industry. The sticker shock has gotten so bad in some parts of Silicon Valley that some companies are reportedly looking to Chinese models for more affordable agentic solutions — despite some concerns over potential security issues .

Hacker News featured Rowboat as a local-first alternative to Claude Desktop.

The project is available on GitHub at rowboatlabs/rowboat.

The post has 48 upvotes and 12 comments in the scrape snapshot.

It reinforces a trend toward self-hosted or local-first agent workflows in the AI tooling space.