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The Spoon

Daily news and analysis about the food tech revolution

Michael Wolf

We Talked With Nectar About Their Plans to Build an AI for Better Tasting Alt Proteins

A few weeks ago, the philanthropic investment platform Food System Innovations announced that it had received a $2 million grant from the Bezos Earth Fund. FSI’s non-profit group NECTAR has been building a large dataset of consumers’ sensory responses to alt proteins, and the grant will help NECTAR to continue working on, in partnership with Stanford University, an AI model “that connects molecular structure, flavor, texture, and consumer preference.” The goal, according to NECTAR, is to create an open-source tool for CPGs and other food industry players to develop more flavorful—and hopefully better-selling—sustainable proteins.

I’d been following NECTAR for some time and have been closely tracking the impact of AI on food systems, so I thought it would be a good time to connect with NECTAR. I’d talked about the project briefly with Adam Yee, the chief food scientist who helped with the project, while I was in Japan, and this week I caught up with NECTAR managing director Caroline Cotto to get the full download on the project and where it’s all going.

Below is my interview with Caroline.

What are you building with this new Bezos Earth Fund grant?

“One of the things Nectar is doing is we just won a $2 million grant from the Bezos Earth Fund to take our sensory data and build a foundation model that will predict sensory. So we kind of bypass the need for doing these very expensive consumer panels, and then also predict market success from formulation. It’s intended to be sort of a food scientist’s best friend in terms of new product ideation.”

For people who don’t know Nectar, what’s the core mission, and how did this AI project start?

“Basically, Nectar is trying to amass the largest public data set on how sustainable protein products taste to omnivores. That’s what we have set out to do. We’re building that, and we are working heavily with academics to operationalize that data.

Over a year and a half ago, we started talking to the computer science folks at Stanford to say, like, what are things we could do with this novel data set that we’re creating? It happened to be around that time that the phase one Bezos Earth grant was opening up for their AI grand challenge. I connected Adam with the Stanford team, and they did some initial work on LLMs and found that it was able to do some of this support for food scientists. They published a paper together that came out in January for ICML, the largest machine learning conference, and we ended up winning that phase one grant, which then allowed us to apply for the phase two grant that we just found out about in October.”

From a technical standpoint, what kind of AI are you actually building?

“I am not an AI scientist myself here, so we are heavily partnered with Stanford and their computer science team, but it is an LLM base. We’re basically fine-tuning an LLM to be able to do this sensory prediction work, and it’s a multi-modal approach. There’s a similar project that’s been done out of Google DeepMind called Osmo for smell and olfactory, and we’re working with some of the folks that worked on that in order to model taste and sensory more broadly, and then connect that to sales outcomes.”

How does the Bezos Earth Fund AI Grand Challenge work in terms of phases and funding?

“It’s the Bezos Earth Fund AI Grand Challenge for Climate and Nature. It’s $30 million going to these projects. There were 15 phase two winners that each received $2 million and have to deliver over two years.

The phase one was a $50,000 grant to basically work on your idea and prepare a submission for phase two. We spent about six months preparing, trying to connect this Nectar data set with sales data and see which sensory attributes are most predictive of sales success, and also connecting the Nectar sensory data set to molecular-level ingredient data sets. Ideally the chain of prediction would be: can you predict sensory outcome from just putting in an ingredient list, and if so, what about sensory is predictive of sales success? We’re working on the different pieces of that predictive chain.”

What does your sensory testing process look like in practice?

“It’s all in-person blind taste testing. In our most recent study, we tested 122 plant-based meat alternatives across 14 categories. Each product was tried by a minimum of 100 consumers. They come to a restaurant where we’ve closed down the restaurant for the day, but we want to give them that more authentic experience. They try probably six products in a sitting, one at a time, and everything is blind, so they don’t know if they’re eating a plant-based product or an animal-based product and then they fill out a survey as they’re trying the product.”

How big is the data set now, and what’s coming next?

“We do an annual survey called the Taste of the Industry. For 2024, we tested about 45 plant-based meat products. For 2025, we tested 122 plant-based meat products. Outside of that, we have our emerging sector research, which are smaller reports. We’ve done two of those, and both have been on this category we’re calling balanced protein or hybrid products that combine meat. We’ve tested just under 50 products total in that category as well.

We’re testing blends of things like meat plus plant-based meat, meat plus mushrooms, meat plus microprotein, meat plus just savory vegetables in general. For 2026, our Taste of the Industry report is on dairy alternatives. We’re testing 100 dairy alternatives across 10 categories, and that will come out in March.”

When you overlap taste scores with sales data, what have you seen so far?

“The Nectar data set is mostly just focused on sensory. That’s the core of what we do. We are also interested in answering the question ‘do better-tasting products sell more?’ In our last report, we conducted an initial analysis of overlapping sensory data with sales data, finding that better-tasting categories capture a greater market share than worse-tasting categories. Better-tasting products are capturing greater market share than worse-tasting products. In certain categories, that seems to be agnostic of price. Even though the product might be more expensive, if it tastes better, it is capturing a greater market share.

We’re currently working with some data providers to get more granular on this sales data connection, because that analysis was from publicly available sales data. In this AI project, we are trying to connect sensory performance with sales more robustly to see which aspects of sensory are predictive of sales success. It’s hard because there are a ton of confounding variables; we have to figure out how to control for marketing spend, store placement, placement on shelf, that sort of thing. But we have access to the Nielsen consumer panel, this huge data set of grocery store transactions over many years, from households that have agreed to have all of their transactions tracked. We’re able to see what consumers are purchasing over time, and we’re trying to connect the sensory cassette to that.”

You also mentioned bringing ingredient lists and molecular data into the model. How does that fit in?

“We’re trying to say, there are a lot of black boxes in food product development because flavors are a black box. We don’t have a lot of visibility into companies’ actual formulations. We’re trying to determine if we can extract publicly available information from the ingredient list and identify the molecular-level components of those ingredients, and then determine if any correlations can be drawn between them.

It’s all of these factors plus images of the products and trying to see if we can predict that.”

What do you actually hope to deliver at the end of the two-year grant?

“The idea is to deliver an open source tool for the industry to use. The goal would be that you can put in all the constraints you have for sustainability, cost, nutrition, and demographic need, and that it would help you get to an endpoint where you don’t have to do a bunch of bench-top trials and then expensive sensory.”

How do you think about open source, data privacy, and companies actually using this tool?

“Data privacy is a big thing in this space. We don’t have any interest in companies sharing their proprietary formulations with us. The goal is that they would be able to utilize this tool, download it to their personal servers, and put in their private information and use it to make better products. If we’re rapidly increasing the speed at which these products come to market and they are actually successful, that would be a success for us.

There are other efforts in this space, from NotCo to IFT. Where does Nectar fit?

“I think everybody is trying to do similar things, but with slightly different inputs and different approaches. We are open to collaborating and learning from people. Our end goal is a mission-driven approach here, not to make a ton of money, so it depends on whether or not those partners are aligned with that goal.

IFT has trained its model on all of the IFT papers that have been published over the many years of its organization being around. We’re training our model on our proprietary dataset around sensory data, so there’s some nuance between things. They’re really focused on developing formulations, but there is a limitation to what you can do with that tool. It’ll tell you, ‘here’s how to make a plant-based bacon, add bacon flavoring,’ but there are 10 huge suppliers that provide bacon flavoring, and it doesn’t provide a ton of granularity on at what concentration and from what supplier.”

What’s the bigger climate mission you’re trying to advance with this work?

“Nectar’s specific directive is, how do we make these products favorable and delicious? We know that we need to reduce meat consumption in order to stay within the two degrees of climate warming, and we’re not going to get there by just telling people, ‘eat less steak.’ We have to use that whole lever and make the products really delicious so that people will be incentivized to buy them more and reduce consumption of factory-farmed meat.”

Answers have been lightly edited for grammar and clarity.

MongoDB Founder Eliot Horowitz on Building a WordPress for Robotics (And Why He’s Skeptical of Humanoids in the Kitchen)

Nearly two decades ago, Eliot Horowitz launched a company with a couple of cofounders that would be pivotal in the early days of big data, helping to create more scalable solutions, lower costs and also reducing the need for deep technical expertise needed in setting up big and messy databases. The company, which would eventually become MongoDB, also gave greater power to the developer community who leveraged the open source model to help iterate and make the product better.

Today, Horowitz hopes to apply many of the ideas that helped make him successful in big data to the world of robotics. With newest company, Viam, he is building a platform he believes will enable software engineers to more easily create and iterate software stacks for robotics and automation systems, a space where the tools to build great software are, in Horowitz’s words, “not great”.

I had heard about Viam because the company’s technology is underlies that of Gambit Robotics, a company building a vision guidance system for the kitchen. In fact, Gambit is also led by Horowitz (as well as former Google AI lead Nicole Maffeo), as a sort of a startup within a startup. In fact, Horowitz and Viam are building other vertically focused solutions on top of Viam for commercial kitchens, boat sanding, fishing and more.

I decided to catch up with Horowitz to talk to him about his move into robotics and how he sees the world of robotics development changing over the next decade. You can read an abbreviated interview below and listen to the entire conversation on The Spoon Podcast. Answers below have edited slightly for clarity.

Why did you decide to get into robotics?

And towards the end of 2020, I was frustrated with how hard it was to bring robotics projects and other hardware projects to fruition and how to make them real. And if you talk to other software engineers, their experiences were not great.

One of the topics you’ve discussed is the critical technology gap between software and the physical world of engineering. How does your new company address that?

What we really saw in this space was that a lot of interesting research had been done over the last 30 years in hardware. Batteries, motors, and robot arms have all gotten much better.

At the same time, the way people build software applications now is completely different from what it was 20 years ago. And a lot of what we saw in the hardware space is things that hadn’t been changed in a while. And it’s different, because with a robotics project, it’s both a big software project and a big hardware project. And when you have tools in the software space that don’t mesh with the hardware tools, and don’t mesh with the robotics and automation side of it, everything gets messy and just doesn’t work.

And so we said, ‘Great, what we’re going to do is we’re going to build a platform that lets engineers actually bring these projects to life.’

In the early days of the Internet, creating a website was not very easy until platforms like WordPress came along. Are you essentially making a WordPress for robotics?

It’s a really great analogy. We joke that if you dropped AWS into the hands of a Perl developer in 1998, they wouldn’t know what to do with it. We’re trying to make that same leapfrog happen in robotics. Wwe want to go from where building a robotics project is an enormous undertaking, where you have hundreds of engineers, to where you can actually build a legitimate production hardware project with real robotics and AI with an actual startup-sized budget.

What did you learn from building one of the world’s most popular database platforms in MongoDB that you are applying to your new startup?

What made Mongo great was we built an incredibly great community that we listened to almost to a fault for a long time around making sure that they were able to build exactly what they wanted and get things done

There are not enough engineers building in this space. And if we can enable more and more engineers to build in this space and really build a platform, lots of people will work together and build great things, and that’s when things get really interesting. It’s our job to enable them to do it and to show them what’s possible so that you can get a million people coming up with really cool ideas and actually bringing them to market. That’s what made Mongo great, and that’s the same thing we want to do here.

Oftentimes the time and the capital needed to bring a robot to market is just years and years and hundreds of millions of dollars. Do you believe you will shorten those timelines and reduce the capital costs by significant degree?

By orders of magnitude. What I see a lot in the robotic startups that haven’t worked is their inability to get to a somewhat interesting proof of concept (POC) that happens pretty quickly. All the engineering you have to do to make it real ends up taking years and years and years. The other big thing we see is the sheer amount of iteration time. Going from one version to the next version takes way too long.

When you can actually iterate fast, when you get a new version, and then another version, when you can test really quickly, or even iterate with users live, that’s when magic happens. And how do you bring that to the robotic space? That’s what we’re really focused on is, how do you bring that iteration time down? How do you get the proof of concept to production time dramatically down?

There are approximately 30 million software engineers worldwide, and most of them are intimidated by working with hardware. Hardware engineers typically have not had great experiences working with software engineers. It just hasn’t gone great over the last 30 years. We’re trying to completely bridge that gap so you can get hardware engineers and software engineers working together in a much more tightly knit sort of cycle and that changes everything.

What do you think about the work on humanoid robotics for the kitchen?

I’m skeptical of that. But a robot arm embedded into the back wall of my kitchen that could manage everything on the stove for me, that could stir things and add some ingredients at the right time or lower the temperature on a burner, that would be really useful. That doesn’t require any breakthroughs. We have the technology and we have the software that we could do today. So there’s a lot of middle steps (to a humanoid) that I think are very practical, very interesting, and can actually move the needle forward very quickly.

You can listen to the full interview by clicking play below or on Apple Podcasts or Spotify.

Cultivated Meat Turbulence Leads to IP Churn Through Deal Making and Open Source Initiatives

Cultivated meat companies spent much of the last decade promising to help fend off the climate crisis while also helping to wean the world off animal agriculture. However, as the industry transitioned from bench scale to pilot facilities and eventually to scaled manufacturing, costs increased and timelines lengthened. This shift happened just as the venture capital world began to pull back on big bets in new areas outside of AI.

The result has been a monumental struggle for cultivated meat startups. Major players, such as Upside and Eat Just, scaled back plans to build large-scale manufacturing plants, while several companies shut down or were acquired.

One interesting wrinkle in this corrective period has been the movement of intellectual property in the form of patents, cell lines, and technical knowledge. As startups look for new paths through acquisition, merger, or wind-down, significant cultivated meat IP is changing hands. In one case, key assets have even been open-sourced. The acquisition activity around IP began in earnest last year, although early signs appeared before that.

Last week, Fork & Good announced it had acquired Orbillion, combining two of the more sophisticated platforms in cultivated pork and beef. Fork & Good has been working on cultivated pork since 2018, and Orbillion, founded in 2020, brings cultivated wagyu beef technology into the fold. The deal creates what the companies say is the largest IP portfolio in cultivated red meat.

“We’re not asking food manufacturers to wait five to ten years for supply chain solutions,” Fork & Good CEO Niya Gupta said in the announcement. “We’re giving them the ability to improve their products right now.”

Orbillion’s CEO Patricia Bubner, now COO of the combined entity, framed the deal as strategic consolidation aligned with a more pragmatic era that is margin-focused, customer-driven, and centered on technical execution rather than R&D alone.

A few months earlier, Meatable acquired Uncommon Bio’s cultivated meat platform, bringing over key technology, cell lines, IP assets, and technical staff as Uncommon shifted toward therapeutics. The acquisition strengthened Meatable’s multi-species lineup and its non-GMO platform, further concentrating Europe’s cultivated meat expertise under fewer roofs.

And just weeks before Fork & Good’s move, Gourmey merged with Vital Meat to form PARIMA. The deal brings “Gourmey’s full-stack industrial platform, which includes premium cultivated duck products validated by Michelin-starred chefs and independently verified production costs below €7/kg, with Vital Meat’s poultry cell-line technology developed from nearly 25 years of avian cell research at Groupe Grimaud, a global reference in animal genetics and biotechnology.”

The merged Paris-based entity unites Gourmey’s cultivated duck and foie gras technology with Vital Meat’s chicken platform, consolidating more than 70 patent filings and regulatory dossiers into a single operation targeting the European market.

Taken together, these deals signal a decisive shift: fewer players, deeper portfolios, and stronger technical moats. The companies that survive are those with enough IP, regulatory traction, and cross-species optionality to prove viable unit economics before pursuing scale.

And Then There’s Open Access

While consolidation was expected, another move announced in October was surprising, both in timing and format.

In mid-October, the Good Food Institute announced it had acquired bovine cell lines and serum-free media formulations from shuttered startup SCiFi Foods and partnered with Tufts University to release them for open research access. The move effectively open-sourced core cultivated beef IP, saving future startups and researchers years of development and millions of dollars.

“By making these cell lines and media broadly accessible to the cultivated meat ecosystem, researchers and companies have a new starting line – one that’s now closer to the finish line of bringing new products to market,” said GFI’s VP of science Amanda Hildebrand. “SCiFi’s pioneering work is like a baton in a relay. Given our role in the field, GFI was able to ensure that baton didn’t drop, and through our partnership with Tufts, copies of that same baton will be handed off to scientists and startups around the world, enabling more people to join the race.”

Joshua March, SCiFi’s co-founder, put it more bluntly: “It took us four years and tens of millions to develop these cells. Now future startups will be able to leapfrog us.”

I sat next to March in the spring of 2024, while in San Francisco, during a tasting of SCiFi’s cultivated meat. At the time, he gave no indication of the company’s financial struggles, but just a couple of months later, SCiFi shut down. Credit to Joshua and the team for working with GFI to make this technology available, potentially enabling breakthroughs for researchers who can use the SCiFi cell lines and media formulations as a jump start.

Cultivated meat still has a long road ahead. Some states have taken an antagonistic stance despite USDA approval for three (now four) companies to sell product in the United States. Investors remain cautious due to long scaling cycles and the challenge of convincing consumers that cultivated meat can be both tasty and healthy. Still, the industry is taking necessary and sometimes painful steps to prepare for the next stage. Combined with promising advances in manufacturing technologies, such as those from Prolific Machines, there is reason to believe the final chapter of the cultivated meat story has yet to be written.

Behind The Scenes at Good Housekeeping With Nicole Papantoniou

Last month I was in New York City, so I decided to drop and visit the Good Housekeeping Institute. I went to visit Nicole Papantoniou, the director of the Kitchen Appliances Lab at Good Housekeeping, who had promised to give me a tour of the place.

If you haven’t visited Good Housekeeping Institute, it’s great because – aside from having one of the best possible views of Midtown Manhattan perched from its location on the 29th floor of the Hearst Building – it’s a cool hybrid of a newsroom meets testing lab, with appliances like air fryers, espresso makers, induction tops and ice cream makers piled high on surfaces everywhere.

“We’re using these items basically the way someone would use them in their home,” Nicole told me on the most recent episode of The Spoon Podcast. “Being able to compare things side by side and then understand the ease of use features, we really get a good understanding of how the product works.”

If you grew up hearing about the Good Housekeeping Seal like me, there’s a reason: for the past century, the publication and the institute helped pioneer consumer product testing. From the time Hearst bought in 1911 until the 1960s, it became a household name, and over the next half century, hitting 5 million in circulation by the 60s.

“In the early 1900s is basically when products were coming to the market and the team members were like, there’s no one really regulating it,” said Nicole. “So really trying to explain to consumers what they should be buying, what they can trust. And that’s what the good housekeeping seal is.”

In a way, being in the Good Housekeeping Lab felt like going back in time. From the different dedicated testing area for appliances, fabrics, and other household items to a full-fledged test kitchen, it was such a big departure from the current way in which most products reviews get generated in 2025, where influencers often will try something out or just see it online and give a review of the product.

According to Nicole, the reviews are around a seasonal rolling calendar which mirrors consumer behavior. “We work three months in advance on print and digital,” she said. “Think of summer… people are going to be searching for ice cream makers. And then think of also Q4, Black Friday, the holidays.”

Some categories, like air fryers, never sleep, while others resurge and periodically come back (stand mixers and bread makers). They also spin up new sub-categories as products evolve.

“We had our espresso maker story forever,” said Nicole. “But now there’s a lot of all-in-one espresso machines. You press your button, you get your cappuccino like you would in a office.”

On the podcast, I asked Nicole how she ended up with such a cool gig. According to her, she had gone to journalism school and knew she wanted to work in magazines, but the inspiration to fuse food and journalism all started with an internship.

“My first internship was at Ladies Home Journal. And I remember going into the test kitchen and someone was grilling pineapple and like candying walnuts. And I was like, how do I get that job?”

From there, she went to culinary school at night while working full time, then moved into brand-side roles. “I ended up at Cuisinart, developing products with them and recipes and helping edit user guides, and then ended up Family Circl and then here at Good Housekeeping.”

She told me that brand experience shaped how she evaluates products today. “When you’re working at a brand, you’re working with so many different departments. An engineer will come up with something really exciting and then you kind of have to hone it in and let them know like, this might not work in like a real consumer’s kitchen.”

I asked her if she had any advice for those looking to get into a similar line of work.

“I think, honestly, getting as much experience as you can with people who are in the field, saying yes to things, taking on different experiences,” she said. “At one point I was working for, like, four different jobs at once… but I loved it. Be nice, and say yes and then you’ll find what you’re looking for. Also don’t be afraid to walk away. There’s a lot out there.”

If you want to listen to my full conversation wtih Nicole you can click play below or find it on Apple Podcasts and Spotify.

Are Big Food Companies Really Embracing AI?

While some companies like NotCo have positioned themselves as the OpenAI of the food world, the truth is that the AI transformation of the food industry is still in the first inning. That is partly because the food system itself, a mix of legacy CPG giants, agricultural suppliers, ingredient developers, and regulators, moves at a glacial pace.

In my recent conversation with Jasmin Hume, founder and CEO of Shiru, she confirmed that the industry is still in the early stages, in large part because food companies have massive amounts of data and strong confidence in their own research and development.

“Food companies have world-class R&D teams, and those scientists want to see proof before adopting a new tool. It’s a lot of tire-kicking in the first meetings,” said Hume.

This slow pace does not mean AI is not making inroads. It is simply happening beneath the surface. From discovery platforms like Shiru’s to optimization tools in manufacturing and retail analytics, AI is slowly reshaping how food gets made.

But the true question is not if the food system will use AI, but who will own the models that make it useful. The answer is usually tied to who owns the data. Legacy food and ingredient companies have decades, even centuries, of proprietary chemical, biological, and sensory data. This makes them both powerful and hesitant to engage with AI models that might use that data to build their own foundation models.

Big food brands “are not going to very quickly turn over that data,” said Hume. Many are debating whether to build their own in-house systems, using models fine-tuned on proprietary data that never leaves their servers. Others are beginning to explore partnerships with companies like NotCo and Shiru that specialize in the discovery layer.

That need for validation may be the biggest differentiator between food AI and other industries. As Hume put it, “You have to bring it into the lab and make sure that it actually works. Otherwise, the predictions are worthless.”

When Hume and I discussed whether large players like Microsoft or Google would eventually dominate vertical-specific foundation models, she acknowledged that possibility. However, she stressed that today’s large foundation models are not yet equipped to deal with the physical and regulatory realities of food. “There’s a ton of very specific know-how that goes into making those models usable for applications like protein discovery or formulation.”

For Shiru competitor NotCo, this highly specific data and domain knowledge are what the company is banking on to solidify its position as a key player in building a foundation model for food, a term now featured prominently on its website.

“I think what people need to understand is that AI is truly about the data sets and the value of the data sets that you have and the logic of the algorithms,” said Muchnick in an interview I had with him in July at Smart Kitchen Summit. “It’s really hard to get to where we were, and specifically also because we weren’t just an AI company. We are a CPG brand, and we learned a lot from being a CPG brand.”

In conversations with AI experts outside of food, several have said we are starting to see the big foundation models open up to allow companies to train them with vertical or highly specific domain knowledge. One pointed to Anthropic’s Model Context Protocol (MCP), which lets a foundation model connect to external data sets to process answers.

Another example is Thinking Machines’ newly announced fine-tuning API called Tinker, which could make it significantly easier for a food brand to train a model with domain-specific knowledge by removing the heavy infrastructure and engineering overhead typically required for custom AI development.

For Shiru, NotCo, and others developing food and ingredient-focused AI, there is still significant opportunity because the field is still so early.

“We’re just starting to see companies thinking about their own internal instances,” said Hume. “A lot of this is in progress, boardrooms are having these discussions right now.”

One of the biggest holdups for food brands is that data ownership and business-model alignment remain unsolved. Who owns the training data and the resulting outputs is a key question, and without clear answers, many companies will hold their data close, limiting the ability of shared platforms to reach critical mass.

For that reason, Hume believes partnerships and licensing models, not open data exchanges, will drive progress in the near term. Shiru’s model focuses on IP discovery and licensing, which allows the company to build intellectual property value without requiring massive manufacturing investments. “Our IP portfolio has doubled year over year since 2022,” said Hume. “Now the focus is on monetizing that through licensing and sales.”

The topic of food-specific foundation models and the adoption of AI by food brands is a fast-moving one, so you’ll want to make sure to listen to this episode to get caught up. You can listen to our entire conversation below or find it on Apple Podcasts, Spotify, or wherever you get your podcasts.

Your Smart Light Bulb Just Told You Your Blood Sugar’s Spiking. Is This The Smart Home’s Next Frontier?

Nowadays, when a smart light bulb shifts from soft white to red, it usually means someone’s at the door, the dog got out, or another home automation routine has been initiated in your smart home app.

In the near future, that same light bulb might tell you the donut you ate for breakfast is spiking your blood sugar.

In some ways, this connection between health tracking devices and the smart home is already happening. One (not-so-consumer-friendly) option is using open-source software like Home Assistant, which allows Dexcom CGM users to create scripts that trigger automations on smart devices based on a predetermined blood sugar level.

There’s also new hardware like the Sugar Pixel, a Wi-Fi–connected alarm clock that integrates with a range of glucose monitors, including Dexcom, Libre, and Gluroo. Many of these connections aren’t through official APIs and are a bit MacGyver’d together, but according to the user guide, you can get your Stelo from Dexcom and other CGMs to send readings directly to the Sugar Pixel.

Startups are also moving into this space. Ultrahuman, for example, is building wellness-sensing devices, like smart rings and glucose monitors, alongside a home hub focused on health. The Ultrahuman hub already measures air quality, temperature, and light. It’s not hard to imagine them linking that hub to their M1 Live glucose monitor or Ring AIR smart ring, creating a home environment tuned around a person’s health biomarkers.

Apple seems like an obvious candidate to lead here, given it has both a smart home framework (HomeKit) and a health framework (HealthKit). But so far, there’s no sign the company is interested in merging the two. That’s not shocking since Apple’s support for the smart home has always felt half-hearted, but it’s still worth keeping an eye on Cupertino for future moves.

For now, these integrations are the domain of early adopters, people comfortable tinkering with open-source software or willing to trust a Wi-Fi alarm clock from a small startup. Long term, though, as CGMs become more democratized and widely used, I expect we’ll see a much stronger connection between wellness tracking and the smart home.

MIDEA Shows Off NFC-Enabled Smart Clips to Help Track Food

Earlier this month at IFA, Midea showed off a range of new smart kitchen gear, including a new refrigerator lineup that features a smart clip system to keep track of food expiration dates.

The smart fridge system, called the INSTA-FIT MASTER, included what the company calls “AI PREPMASTER” and the NFC clips “AI Food Clips”. The clips, which include an NFC communication chip, can be assigned to different food items by the home user within the app.

As can be seen in the video above, users of the new fridge deploy a new NFC smart clip by walking through a series of choices in the app, such as food category (meat, dairy products, vegetables, etc), where the food is stored (freezer, refrigerator) and recommended storage duration. According to MIDEA representative Haoyu Wang, the light in the clip storage rack will turn red when the food is hitting the end of its freshness window.

In some ways, the MIDEA clip system is reminiscent of the Ovie smart clip system, only unlike Ovie the system is integrated with the fridge itself. To our knowledge, it’s the first effort tby an appliance maker to use a fridge-integrated clip system for food tracking. Other smart fridge efforts to track food often featured built-in fridge cams and/or an app in which consumers logged food as they put it into the fridge.

The company indicated that the AI Food Clips and the AI PREPMASTER system will chip in 2026.

DoorDash Rolls Out Delivery Robot and an AI- Powered Delivery Orchestration Platform

There’s a new delivery robot in town, and its name is Dot.

DoorDash announced the new delivery bot today, confirming months of rumors that they were working on their own robot. The robot, developed entirely by its internal DoorDash Labs team, is the delivery company’s first homegrown bet on delivery automation and street-level autonomy, signaling the company sees owning more of the underlying robotics stack that powers delivery as a strategic priority.

Dot, which is roughly one-tenth the size of a car, can reach speeds up to 20 mph. DoorDash claims the system is designed to travel across sidewalks, bike lanes, and neighborhood roads, providing it with flexibility in navigating mixed urban environments. Watching the video of the Dot (see below), it’s clear that the robot really moves.

“(Dot) is small enough to navigate doorways and driveways, fast enough to maintain food quality, and smart enough to optimize the best routes for delivery,” said Stanley Tang, Co-Founder and Head of DoorDash Labs. “Every design decision, from its compact size to its speed to the sensor suite, came from analyzing billions of deliveries on our global platform and understanding what actually moves the needle for merchants and consumers.”

As part of the Dot rollout, the company also introduced it’s Autonomous Delivery Platform (ADP). The company describes ADP as an AI-driven dispatcher that selects between human Dashers, robots, drones, or other modes based on order type, distance, and merchant requirements.

The company described its effort to build out the autonomy stack in a post on its engineering blog. According to the company, Dot continuously ingests multi-modal sensor data (LiDAR, cameras, radar) to detect obstacles, classify terrain, and localize itself within complex urban settings. That raw sensor input feeds into a perception module, which constructs a dynamic environmental model, identifying pedestrians, street furniture, curbs, driveways, and motion patterns of nearby agents. Above the perception player lies the planning layer, which reasons about safe and efficient paths, lane transitions, sidewalk maneuvers, and mode switching (e.g. segueing from bike lane to sidewalk). Finally, the control or actuation layer translates those planned trajectories into smooth motor commands, ensuring payload stability and maintaining robust compliance with safety constraints.

In a way, the announcement of ADP as an orchestration layer is perhaps more interesting than the debut of a DoorDash native delivery robot, as it marks a big move forward for DoorDash to build a multimodal delivery network managment system. The system will streamline “handoffs today while laying the groundwork for more reliable, efficient deliveries as autonomy scales.” The company stated that it plans to work with third-party delivery technology companies (like, perhaps, drone delivery as well as other sidewalk delivery companies like Coco, with which it has already partnered).

With DoorDash’s announcement, it’s work looking at the potential impact on the delivery company’s third party technology partners such as Coco Robotics. DoorDash launched its partnership with Coco Robotics, whose bright pink sidewalk robots have been operating under the DoorDash app in Los Angeles and Chicago since 2021. While DoorDash says it plans to work with third-party providers, framing of Dot as “purpose-built for local commerce” suggests a long-term intent to shift from relying on external robot vendors to deploying its own fleet.

After the publication of this story, a DoorDash representative reached out with a comment on their relationship with Coco and other partners: “Coco is a long-term partner, offering sidewalk robot delivery for DoorDash customers in select U.S. markets – including Los Angeles, Miami, and Chicago – as well as in the EU, in Helsinki – and we’re focused on continuing to scale that partnership. Built for dense urban environments and sidewalks, Coco is designed to handle a range of delivery scenarios. With DoorDash handling millions of deliveries a day, different types of robots are required for different situations – from dense urban areas to suburban neighborhoods – which is why our multimodal strategy is so important, and why Coco is an integral part of that strategy.“

You also have to wonder if DoorDash’s move to create its own delivery bot is an answer to Uber’s strategic partnership with Serve. Some might remember that Serve, which Uber acquired when it acquired Postmates, was spun out of Uber in 2021, and that Uber still owns a stake in Serve Robotics and that the two companies work closely together.

Scott Heimendinger Wants to Reinvent a Two Million Year Old Kitchen Tool by Making it Vibrate (Really Fast)

If you were to bet on what the oldest kitchen tool in existence is, you’d be smart to put your money on the knife. It’s not just centuries old but tens of thousands of centuries old, as humans have been using sharp objects to cut food for over two million years.

So when someone says they want to reinvent something that old, it’s natural to be skeptical. After all, what exactly can you do to a knife to make it better at what it does?

If you ask Scott Heimendinger, he’d tell you that adding ultrasonic technology to a knife can actually improve this ancient tool. Heimendinger, who previously founded a consumer sous vide startup in Sansaire, has been working on doing just that for more than half a decade, and today he announced that end result of all that work is now on sale and will ship early next year.

So what exactly is an ultrasonic knife? If you’re familiar with ultrasonic toothbrushes, it’s similar in that ultrasonic energy creates thousands of vibrations per second. In fact, according to the announcement, the knife (called the C-200) will vibrate 40 thousand times per second.

Given the time and energy invested, I asked Heimendinger if he was nervous about launching a new product despite being a startup veteran.

“Of course I’m nervous,” he said. “This is a thing I’ve been working on for nearly six years and it’s gonna see daylight for the first time ever. And I’m totally nervous. I have so much of my heart and soul poured into this thing and money and literal blood.”

Since it’s been more than a decade since his first product launch with Sansaire, I also asked him how the landscape for smart kitchen products has changed since then.

“In 2012 and 2013, the Modernist cooking movement was really sort of on an upward trajectory,” said Heimendinger. “Now, I think that the more prevalent movement in cooking, especially home cooking, is not more technology but less. It’s sort of a return to analog in a whole bunch of ways.”

If that’s the case, why add ultrasonic technology to a knife? According to Heimendinger, one of the truisms in the world of kitchen tools is that they must make a cook’s life easier, not harder. Smart kitchen tech, done poorly, just adds more steps. With his knife, those thousands of invisible vibrations per second help make cutting up to 50% easier.

“It was so important to me to design a product where all you have to do is touch a button,” said Heimendinger. “That’s it. There’s no phone pairing. There’s no Wi-Fi setup. There’s no anything. And you can use it when it’s off, as its also a really good analog knife.”

Still, even with the focus on simplicity of use, Heimendinger realizes the knife community can be skeptical, and not everyone will be ready to welcome something like an ultrasonic knife.

“The knife community can be dogmatic in certain ways,” he said. “I know that there’s going to be some people who think that (adding ultrasonic tech) is anathema to the sanctity of a pounded piece of sharp metal. But I hope that they’ll be able to see that I’m taking this quite seriously. And if we want to have a conversation about what actually makes cutting easier for home cooks, then there’s data to support this does just that.”

According to the announcement, the blade is made from Japanese AUS-10 san mai stainless steel that’s durable and corrosion-resistant. The button and grip are suitable for both right- and left-handed users, and the blade can be re-sharpened just like a traditional knife.

The product will retail for $399. Production of the first batch begins in November, and pre-orders open this week on seattleultrasonics.com, with deliveries expected in January 2026.

Samsung Rolls Out Ads to Family Hub Fridges

Samsung confirmed this week that they have rolled out an over-the-network software update to Family Hub refrigerators in the US that will enable advertising on the fridge’s video display. The ads, which will be introduced as cover screens, which are essentially screen saver images that the fridge displays when the screen is idle.

Samsung’s ad plans were first uncovered by a sharp-eyed Reddit user, who posted an image of the software change log.

Android Authority confirmed with Samsung that they are rolling out ads to Family Hubs, and the official statement also disclosed that this rollout is currently only a pilot:

As part of our ongoing efforts to strengthen that value, we are conducting a pilot program to offer promotions and curated advertisements on certain Samsung Family Hub refrigerator models in the U.S. market.

As a part of this pilot program, Family Hub refrigerators in the U.S. will receive an over-the-network (OTN) software update with Terms of Service (T&C) and Privacy Notice (PN). Advertising will appear on certain Family Hub refrigerator Cover Screens. The Cover Screen appears when a Family Hub screen is idle. Ad design format may change depending on Family Hub personalization options for the Cover Screen, and advertising will not appear when Cover Screen displays Art Mode or picture albums.

Advertisements can be dismissed on the Cover Screens where ads are shown, meaning that specific ads will not appear again during the campaign period.

I’m actually surprised Samsung took this long to roll out ads. While some consumers will no doubt find them annoying, the opportunity to push ads in front of consumers via a fairly unique screen location will likely prove profitable for Samsung and worth the risk of alienating a small group of their user-base.

And while it’s currently a pilot, my guess is they’ll roll this out to all Family Hubs over time. I’m intrigued to see where they take it, as I can see them offering potential partner discounts (with, say, grocer or food delivery partners), as well as taking a page out of Amazon’s book for its Kindle “with ads” pricing model, where it essentially offers a discounted device with advertising.

Fresco Partners Up With E.G.O. to Accelerate Smart Kitchen Software

As a former semiconductor analyst, I realized one truism of the tech world: makers of component building blocks for any hardware product eventually move up the stack, integrating with software solutions so their OEM partners see them as the preferred foundation on which to build their products.

So it’s not surprising to hear that one of the world’s leading makers of induction cooking hardware, E.G.O., has partnered with Fresco, a company that provides software to enable smart kitchen hardware solutions. The deal, announced at IFA last week, will allow E.G.O. to add smart kitchen functionality to its induction cooking systems and appliance control systems.

For Fresco, the partnership makes it possible to fast-track appliance partner integration. Because the software is integrated at the component level, it will require less customization for each new system powered by their smart kitchen software.

“We realized instead of trying to partner with all of the brands individually, that it’d be much smarter to go to the source,” said Ben Harris, CEO of Fresco, in an interview at IFA. “So we met E.G.O. here a year ago and aligned on the potential future of a partnership. I’m delighted to be here at IFA to now announce the kickoff of the partnership and sort of where this can ultimately go.”

According to Harris, the partnership means Fresco no longer needs to integrate one-on-one with dozens of different brands. Instead, by working directly with E.G.O., Fresco’s technology can come “available out of the box.” Harris explained: “It’s two things, both from a sales point of view, that we don’t need to speak to all hundred brands, but also we don’t need to do the small individual integrations with every one of them. The integration is available out of the box.”

It has been interesting to watch Fresco (formerly Drop) evolve from its early days as a maker of a connected kitchen scale to a software company that, historically, had to do significant customization for each appliance partner. With its new partnership with E.G.O., my guess is this will accelerate their partner growth while also making a smart software/connectivity stack a more standard part of the broader bill of materials for new appliances.

Fresco has remained fairly true to its early focus (post-scale) of being a smart kitchen software ingredient provider, while others like SideChef and Innit have focused more on commerce and, more recently, food and wellness-related AI solutions for CPG partners..

You can watch my conversation with Ben Harris at IFA below.

Fresco's Ben Harris Talks New Partnership with E.G.O at IFA

Apeel Sues Online Influencer In Latest Effort to Stem Tide of Misinfo About Produce Life Extension Tech

Apeel, a maker of produce life-extension technology, announced this week that it is suing an online influencer who had spread misinformation about the company’s product for the last two years.

The company, which earned early recognition in the food waste innovation space for its non-toxic, plant-based coating that helps extend the shelf life of vegetables such as avocados, has faced a growing wave of misinformation in recent years. Conspiracy-peddling online influencers have claimed the company’s product contains everything from gasoline-like chemicals to heavy metals.

Because of this, the company has gone to battle against one influencer in particular: Robyn Openshaw, who goes by the name “Green Smoothie Girl” on Instagram and other platforms. Apeel filed suit on August 29, 2025, in the U.S. District Court for the Middle District of Florida, accusing Openshaw of publishing at least 60 posts between July 2023 and May 2025 across Instagram, YouTube, X, Rumble, and her own website. The posts alleged that Apeel’s coatings contained palladium, mercury, arsenic, and other heavy metals.

According to Apeel, Openshaw told her followers to boycott Apeel produce, urged retailers like Costco and suppliers such as Driscoll’s to avoid the product, and even sold a downloadable “wallet card” listing stores not using Apeel.

Openshaw was not the only voice on social media making such claims. Alongside countless smaller accounts, actress Michelle Pfeiffer also posted about the technology and incorrectly claimed it was owned by Bill Gates. After what appeared to be legal and PR interventions, Pfeiffer later posted a correction:

“Ugh! For any of you who reposted or shared my story about Apeel it turns out that I unintentionally reposted inaccurate and outdated information, and I’m very sorry for that,” wrote Pfeiffer via an Instagram story. “@apeel_sciences has informed me that The Bill & Melinda Gates Foundation awarded two research grants to Apeel Sciences and Gates has no role with or ownership in Apeel. And regarding their organic product, Organipeel, Apeel told me it was not JUST approved but was first allowed back in 2017, though it has not been offered commercially in any market for over two years because they have been working (through proper protocol) on new organic formulations to meet the evolving needs of the organic industry. … Public conversations about food safety and sustainability matter deeply, but they’re only as helpful as they are accurate. Thank you! Xx m”

And it is not just online influencers and ’90s-heyday actresses that have targeted Apeel:

Republican Congressman Marlin Stutzman’s initial concern was the involvement of the right-wing boogeyman and former Microsoft CEO Bill Gates.

“I think that the red flags went up for me when I saw that the Bill and Melinda Gates Foundation was behind the development of this product,” said Stutzman in a Facebook post.

The Gates Foundation awarded about $1.1 million in research grants to Apeel in 2012 and 2015 as part of its broad philanthropic efforts. In those two years alone, the foundation gave away over $7 billion across a wide range of organizations and projects.

Stutzman went on to claim Apeel was not being transparent about its ingredient list and introduced HR 4737, also known as the Apeel Reveal Act. The bill seeks to amend the Federal Food, Drug, and Cosmetic Act to require disclosure of certain product coatings used on fruits and vegetables.

Despite being pretty open about what is in its coating, the company has spent millions on marketing and PR to combat confusion related to online misinformation, much of which dates back to 2023 when Openshaw and other influencers circulated the ingredient list of an entirely different product: an industrial cleaner from UK company Evans Vanodine that shares the name “Apeel.”

If you’re wondering whether the wave of misinformed influencers and posturing politicians has affected Apeel’s business, the answer is yes. Regional retailers such as PCC have issued statements on their websites noting they believe Apeel is generally safe, but they have nonetheless instructed their distributors not to source produce that uses Apeel. Others, like Sprouts and Publix, have also said they will not purchase Apeel-coated produce.

While many of these retailers probably agree with Apeel that their product is not harmful to humans, you can’t blame them. Trying to educate shoppers in an era where social media is the primary channel for many consumers when it comes to food and nutrition information is a losing battle. Today’s social channels are rife with lots of bad information from self-proclaimed experts, and grocers probably figure this is one less battle they need to fight.

As for Apeel, the lawsuit may reveal whether legal action can help stem the tide of misinformation. In an era where even our own governmetn traffics in misinformation, the company has an uphill battle ahead.