One of the most important things happening on Earth today is the solar energy build-out. Around the world, companies and countries are racing to deploy solar and batteries to achieve energy independence and limit the effects of climate change.

That build-out, though, is running into a labor market challenge, with a limited supply of workers to meet a growing demand for installation. Robots could be an answer, but industrial robots have historically struggled in unstructured environments, at least until now. The latest generation of AI models may have changed that equation.

That’s the driving idea behind Gritt, a start-up founded by two Carnegie Mellon-trained roboticists, CEO Puneet Puri and CTO Vishal Dugar. The company exited stealth Tuesday morning with a $26 million Series A round of funding led by Obvious Ventures with participation from Union Square Ventures and Active Impact Investment. That brings its total funding to $34 million, following an earlier seed round backed by First Round Capital, Climactic, Congruent Ventures, and VSC Ventures. The startup is building an intelligent system to “help civilization build infrastructure faster,” in Puri’s words.

“Our thesis is that if we truly want to speed up construction,” Puri tells TechCrunch, “you need an intelligence which can work in the outdoor, chaotic environments of these construction sites, and it has to be generalizable enough that it can work in these varied environments.”

Rather than building its own robots from scratch, Gritt uses off-the-shelf hardware—thus far, rented skidders and robotic arms built by companies like Kawasaki—to build platforms that are controlled by its AI models. The first job its systems handle is unloading large, glass solar panels, carrying them toward the metal frames where they need to be installed, and positioning them on the frames with sub-millimeter accuracy so workers can fasten them.

“There are people who used to build rockets that went into space and had infinite budget for the smallest little part, and then there are people who know what it means to get into dirty, dull, and dangerous jobs and scale them like mad,” said Andrew Beebe, the partner at Obvious Ventures who led Gritt’s Series A round. “These guys are in the second camp, and that’s a special kind of entrepreneur that has the technical chops, the AI, and the machine vision skills to make it work.”

Gritt has two systems currently deployed in the field, using the data they collect to improve their behavior. Puri says that a typical eight-person crew workers can install 800 panels a day, but the same crew working with Gritt’s systems can install 3,000 to 4,000 panels each day.

Now, the company says it is contracted to help install 2.8 gigawatts of solar panels in the next 18 months, and that its customers include three of the top 10 US power construction companies. The company hopes to be operating 48 of its systems within the next six months.

TechCrunch spoke to one Gritt customer who declined to be identified for competitive reasons, but who was enthusiastic about the system’s ability to improve his work. He expects it to be easier to work at remote sites where it is difficult to attract workers, and anticipates a reduction in injuries since workers won’t have to repeatedly lift 100-pound panels overhead.

Gritt is competing against companies with their own panel-installing robots like Luminous Robotics, Cosmic, and China’s Trinabot. Those companies are building their own hardware, rather than focusing on off-the-shelf vehicles and arms like Gritt, a difference that could shape who grows faster and with a leaner cost structure as demand grows.

Gritt wants to add new manipulation tasks to its system so it can fasten the solar panels, drill posts, and even build the racks they sit on. Longer term, it also wants to move into other common, labor-intensive construction tasks, like tying rebar before concrete is poured over it.

What’s enabled the startup to pursue this vision? Mainly, the rise of new AI models, the founders say.

“Making a system for one solution was still possible to some extent five years ago, right?” Puri said, but AI is now making that work generalizable — the same underlying pipeline can be reused and improve across tasks. As an example, he noted that training the system to stack cinder blocks took weeks, while a similar demo with rebar tying took just a day using the same software.

But training new tasks is just the beginning of Gritt’s vision. The founders believe the suite of sensors and intelligence its systems bring to worksites can do more than install panels; it can boost management and decision-making. For instance, they imagine their system noticing a trench is open while a storm approaches, allowing it to alert workers to cover it before rain damages components, or flagging missing inventory.

“Gritt becomes now this layer of physical AI, which is doing this dextrous, labor-intensive task, plus it can help you take decisions on the site,” Puri said.

Anthropic can finally start cutting checks to a group of authors and book publishers that sued the AI lab over copyright infringement. A federal judge gave final approval Monday of Anthropic’s landmark $1.5 billion settlement of a class action copyright lawsuit, Reuters reported.

Judge William Alsup of the U.S. District Court for the Northern District of California issued a preliminary approval of the settlement last year, after ruling that Anthropic had illegally downloaded and stored millions of copyrighted books.

Alsup has since retired and Judge Araceli Martinez-Olguin signed off on the settlement on Monday.

The payout will deliver $3,000 per work across an estimated 500,000 works, shared among the authors and publishers who hold rights to them. While the settlement is believed to be the largest in the history of U.S. copyright law, many authors and creators still don’t view it as a win.

That’s because of how the legal question was resolved. Alsup sided with Anthropic on the core issue. He ruled that training an AI model on copyrighted text counts as fair use — a decision widely seen as a turning point for the AI industry. But the ruling didn’t excuse how Anthropic obtained the books in the first place. Anthropic had built its training library from two sources: books it purchased and scanned (fine), and books it downloaded from pirate sites like Library Genesis and Pirate Library Mirror. Alsup found the second method illegal on its own terms and said that piracy question could go to trial; Anthropic agreed to a settlement soon after to avoid a trial and whatever damages a jury might have awarded.

While the final approval closes out this case, it doesn’t settle the legal question industry-wide because Alsup’s ruling was a single district court decision, and Anthropic’s decision to settle means the case will never reach an appeals court to become binding precedent.

Other judges are still free to reach their own conclusions on their own facts, which is exactly what’s playing out elsewhere. There is still a string of copyright lawsuits against companies such as Google, Meta, Midjourney, and OpenAI over whether it’s legal to train AI models on copyrighted works. Just last week, a group of publishers and authors, including Hachette, Cengage, Elsevier, author Scott Turow, and S.C.R.I.B.E. filed a class action lawsuit against Google over accusations that the company used their copyrighted works to train its AI platform, Gemini.

When de-extinction startup Colossal Biosciences revealed last year that it was attempting to “resurrect” the dire wolf from genetic material found in fossils, we argued that, despite the controversy surrounding the project, the company was building valuable technologies that justify its $10.2 billion valuation.

Now, roughly 16 months later, the startup is in talks to raise new funding at a $20 billion to $30 billion valuation, Axios reported.

It’s not clear who is leading the new round, or how much capital the five-year-old company is looking to raise. But we do know, according to the report, that Colossal has started generating revenue over the last year.

Colossal co-founder and CEO Ben Lamm told TechCrunch last year that the company sees three revenue streams for the business.

The company has offered its conservation technology to the U.S. government and the UAE, which recently invested $60 million in the company, according to Wired.

Colossal has spun out three startups, including Breaking, a company that helps break down plastics; Form Bio, a computational biology platform that secured $30 million in funding; and Astromech, an AI-driven predictive modeling company focused on biology and life sciences, which was valued at $2 billion in March.

Lamm told TechCrunch last year that the company also plans to spin off its artificial animal womb technology, which could have applications for human fertility treatment. In May, he told Rolling Stone that the technology is expected to be ready next year.

If the company manages to reintroduce extinct animals, including the woolly mammoth and the dodo bird, to their native habitats, it may eventually generate revenue through the sale of biodiversity credits, a market-based mechanism similar to carbon credits, according to Lamm.

The new fundraising effort comes amid a boom in longevity tech, alternative energy, and other deep-tech sectors.

Colossal didn’t respond to our request for comment.