Science Corporation CEO Max Hodak announced that the company has implanted its vision-restoring chip, PRIMA, into its first patient with Stargardt disease, an inherited eye disease that gradually destroys central vision. Hodak, the former president and co-founder of Neuralink, the brain implant company, explained on stage at TechCrunch Disrupt how the company’s work with PRIMA fits into its broader pursuit of a novel brain-computer interface (BCI).

“The retina is part of the central nervous system,” Hodak said on stage. “We consider cochlear implants, retinal prostheses, motor prostheses, these are all different types of BCIs.”

Hodak outlined a vision in which BCIs expand into a wide range of medical technology applications, rather than simply being a way to control computers.

While PRIMA is commercially available in Europe for patients who’ve lost their sight to geographic atrophy, an advanced form of age-related macular degeneration, the company believes its approach can be applied to multiple diseases, including Stargardt disease, which is currently considered incurable.

Stargardt disease affects the outer retina, causing the gradual death of the eye’s light-sensing cells while potentially sparing the inner retina, the part that passes visual signals onto the brain. It causes a central blind spot that gradually enlarges over time. Approximately 150,000 people worldwide have lost vision due to the disease.

“One of the nice things about this device approach, when I was saying the brain’s a computer, vision is electrical potential, like electrical activity down the optic nerve,” Hodak said. “That’s all vision is to the brain, and so if you can get the optic nerve to signal the the rest of the brain correctly, then you can provide vision to it.”

The company says its first patient with Stargardt disease received the PRIMA implant in May as part of its ongoing trial at the Sydney Eye Hospital in Australia. During the patient’s first rehabilitation session, he saw a letter, and during the second, he was able to read a word.

To use the device, patients undergo an hour-long procedure that plants a small chip in the back of their eye, where the photoreceptors have degenerated. Then they wear camera-equipped glasses that transmit a view of the world to the chip. The implant essentially works like artificial photoreceptors.

“The device that this patient has is a two millimeter by two millimeter implant placed under the in the back of the eye, and so it’s like looking through a straw,” Hodak said. “It is not a big field of view color vision. It’s a patch in their central vision where . . .it’s black and white, but it is sharp. It’s high-contrast sharp, and so they can see a couple letters at a time. The next step is to make the field of view bigger. So to make a bigger implant, you have to deal with the curvature of the eye, and we need to make the electrodes smaller so that we get closer to native levels of detail.”

He continued, “I think we have a clear path. There’s a there’s a next ‘next generation’ that’s being worked on that’ll be in humans in the next year, and over the next five years, I think we’ll be able to get pretty close to native acuity.”

When Hodak founded Science Corporation in 2021 after leaving Neuralink, the company outlined plans to develop advanced neural engineering and brain-computer interface technology. But first, the company wants to prove its methods work and develop a sustainable business, which is why it’s working to restore vision with the visually impaired.

As for Science Corporation’s brain-computer interface technology, it has previously said that its sensor will be implanted inside the skull and rest on top of the brain, unlike a Neuralink device, which is inserted directly into brain tissue.

The company has said it believes the device could help address neurological conditions, such as possibly monitoring neurological activity in patients with brain tumors.

“In the near term, we’re going to be applying our first clinical indication, which hasn’t been announced publicly, is a neurodegenerative disease that everybody’s heard of,” Hodak said. “We’re also looking at stroke. For example, if you’ve lost part of your brain because it’s been dead due to stroke, if you can get connections into the deep brain in two different areas, you can imagine adding new cortical areas, just like adding new brain areas entirely — something simply not possible with conventional electrodes. But, I’d say longer term, the long-term mission of the company is to understand how the brain creates the mind and to learn to build engineered brains.”

Hodak went on to note that Science Corporation’s belief is that many people will eventually use some kind of BCI. While the company isn’t designing for “healthy 40-year-olds,” he said, it believes people will eventually need some kind of BCI by the age of 60 or 70.

“We want to figure out how do we extend not just lifespan but health span,” Hodak said.

Cerebras Systems CEO and co-founder Andrew Feldman believes we’re nearing a future where everyone will have an AI appliance in their own home.

Speaking on stage at TechCrunch Disrupt 2026 on Tuesday, the chipmaker executive answered a question about what would need to happen for AI to become a home appliance, saying, “Actually, I don’t think that’s very far away.”

He pointed to the advances in consumer AI agents, like Meta’s Muse and Instinct, the startup now valued at $10 billion, as examples of how AI is finding its footing with everyday users.

As for home AI? He predicts that we’ll have personal AI assistants that run locally.

“Just like your cell phone, they’ll do some work on device and some work going back to the cloud,” Feldman explained. “But I think they will get to know you very well, and you will have a security perimeter around them. And they will certainly have access to credit cards and be able to buy things for you,” he continued. “I think they will make a meaningful impact in making our lives better.”

Of course, for an AI chipmaker, the vision of a home AI appliance, or at least widespread consumer adoption of agentic technology, is certainly appealing.

But Feldman isn’t just working on the hardware infrastructure; he’s a personal AI user himself, saying that he now uses “a collection of agents” to sweep his calendar, pull up information about the people he’s going to have a call with, and more. While AI is already doing many of the things we used to do manually, Feldman is most excited about the new possibilities — things that weren’t possible before.

He’s leaving it up to other founders to figure out what those might be, though.

“One of the reasons I love being in infrastructure is because I don’t need the consumer-facing idea … I like building the platforms that other people’s ideas take flight on,” he said.

In most factories, automation is fixed: robots and machines are programmed for one specific task and product. Changing a line means reprogramming and physical retooling, or swapping out equipment, which can take weeks or months. San Francisco-based Industrial Next says it’s changing that.

The startup, which presented today on the Startup Battlefield stage at TechCrunch Disrupt 2026, builds AI-driven, self-contained robotic stations powered by proprietary foundation models that connect vision, task context and motion. The company says this lets a production line be retooled in minutes rather than weeks without traditional programming. The goal is to let manufacturers automate complex and delicate tasks that traditionally require human labor.

The company announced on stage that it’s partnering with BMW Group Technology Office to evaluate Industrial Next’s AI-powered dexterous manipulation for manufacturing.

Industrial Next was founded in 2021 by Lukas Pankau and Allen Pan, both of whom previously worked at Tesla. Pankau served as a lead electrical architect at Tesla before moving on to Waymo. Pan led Tesla’s autonomous factory efforts and later became a chief architect at autonomous driving company Neolix.

The pair came up with the idea for Industrial Next while working together at Tesla. Pankau’s first encounter with Pan was literally tripping over him as Pan was asleep on a factory catwalk after pulling an all-nighter. Although the two didn’t get along at first, they soon realized they shared an obsession with getting things done and had complementary skills. 

After years of watching cutting-edge vehicle and self-driving technology get held back by decades-old factory equipment, the founders realized that manufacturing needed to be rebuilt.

“We had all these fancy things that we could do on cars. I could run machine learning algorithms to design a car for me. But I couldn’t figure out how to program a robot, and this was pretty common for engineers at Tesla,” Pankau said. “You had this massive divide, right? You had people who are really good at what they’re doing–designing cars and designing self-driving systems–and then you had them effectively stumped at the factory looking at this equipment from the 1980s. And so we started rethinking what this should look like using the technology that we have today and using everything that we know today.”

The two kept thinking about their frustrations with industrial equipment even after moving on to their next jobs. They stayed in touch, often reminiscing about the machines that never functioned the way they wanted, and eventually decided they could do better.

“I was at Waymo at the time, kind of bored out of my mind because I was missing that pace of Tesla,” Pankau said. Pan, he added, was in a similar position at Momenta, a developer of self-driving systems in China. Pan recalled their conclusion: “We’re like, we’re not getting any younger, and we’re still obviously passionate about it. We still keep complaining about industrial technology. Like, this is three years later, we should start the company.”

Pankau notes that traditional industrial robots are typically programmed to perform highly specific, repeatable tasks. As a result, even a small change in the process or product can cause the robot to fail or trigger costly downtime, which forces manufacturers to simplify their products for repeatability.

Making robots truly flexible presents a different challenge. They need enormous amounts of training data and, unlike AI models trained on the internet, robotics lacks the vast datasets needed to teach machines how to perform complex physical tasks. 

“We can make robots do all these cool things like dance around, because there’s data for that, but we can’t make them assemble high-precision things,” Pankau explained. “This is where we’ve made a lot of progress on using simulated environments to do these high-precision and high-dexterity tasks. The secret sauce for the robots that we have is that we have given them an understanding of the process in general, but we build that understanding using an extremely high-fidelity simulation engine that is close to the real dynamics to where we can let the robot do these kinds of high precision tasks almost without seeing the parts at all.”

In other words, the robots practice in a highly detailed virtual world that closely mimics real-world physics. Industrial Next’s robotic stations can be reconfigured, combined, and redeployed across product lines. New tasks are taught through simulation and demonstration, rather than hard-coded scripts. 

Pankau explained that some of the startup’s workstations are already used in making one of the world’s most popular smartphones. They handle tasks that manufacturers had tried and failed to automate for years, such as threading a delicate flex cable and snapping a tiny connector cap into place. (He wasn’t at liberty to disclose the customer.) He also described a “film peeling” station, where their AI-powered robots strip protective film off camera modules and buttons at or above human speed with 100% accuracy, even when moved to a new phone model and production line they have never seen.

“We started this company because that is the kind of performance that we wish we had at Tesla, where we were bypassing robot stations because we couldn’t program them effectively enough using traditional technologies,” Pankau said. “Now we want to take this to more complicated tasks than just building a phone. We ultimately want to take this to building a full car end-to-end without any human touching ever.”

To check out more of the Startup Battlefield — along with a slate of established founders and VCs whose takes on the industry you won’t want to miss — join us at Disrupt, happening this week in downtown San Francisco.