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Fast Company

NBA announces it’s using smart basketballs and wearable tech in preseason games

6 days 1 hour ago

The NBA is experimenting with two pieces of technology in the leadup to the season, the league announced Monday.

Select exhibition games will include a smart basketball that has a Bluetooth sensor in it and can collect data for future use in real-time officiating decisions. The league said the information from the Wilson-developed connected balls will be for research only and not affect calls made during those games.

Officials in select games will also use wrist wearables to communicate with the replay center in designated situations, including replay reviews, scoring changes and clock malfunctions.

The wearables went through what the NBA called a successful pilot program during the summer league. The technology will not extend into the regular season.

—Associated Press

Associated Press

Starbucks hit with a class-action lawsuit over its ‘sugar free’ protein drinks

6 days 3 hours ago

Starbucks is facing a consumer lawsuit over claims that the protein drinks labeled “sugar-free” on its cafe menus may actually contain more sugar than a Reese’s peanut butter cup.

The federal lawsuit filed late Friday in Seattle alleges that eight protein beverages Starbucks sells in the U.S. contain varying amounts of sugar even though the company lists them as sugarless.

On Monday, the menu on Starbucks’ U.S. website listed a 16-ounce (0.5-liter) Sugar-Free Caramel Protein Matcha with 16 grams of sugar and a 20-ounce (0.6-liter) version of the same drink with 21 grams of sugar. By comparison, one Reese’s cup has 11 grams of sugar.

Hagens Berman, a law firm that specializes in class action cases, filed the suit on behalf of three individual consumers who bought Starbucks’ sugar-free protein drinks in California, New York and Washington.

“Consumers avoid sugar for various reasons, whether that be general health, diabetes and blood glucose levels or other factors, and for many, a staunch mislabeling like this is significant,” said Steve Berman, a co-founder and managing partner of the Seattle-headquartered firm.

The plaintiffs contend that Starbucks’ naming and marketing of sugar-free products is “false, deceptive and unlawful” and that the company violated federal labeling regulations.

Seattle-based Starbucks said the sugar in its protein drinks comes from the protein-boosted milk it uses. The company said it doesn’t add sugar to the drinks and it uses sugar-free syrup for flavoring.

On Starbucks’ website Monday, the drinks were marketed as “sugar-free,” but the company also clearly stated the amount of sugar in each beverage and that they were made without added sugar.

“We believe these claims have no merit,” a Starbucks spokesperson said Monday. “Starbucks has consistently and clearly provided information about its protein beverages, sugar-free options, customization choices and nutritional content across product announcements, menus, marketing materials, Starbucks.com and the Starbucks app, and we intend to vigorously defend ourselves in this matter.”
Starbucks introduced its protein drinks in September 2025 to meet consumer demand for functional beverages and catch up to rivals like Dutch Bros, which launched protein-enhanced coffee drinks in 2024.

Dutch Bros also offers a lower-sugar version of its caramel-flavored Hopscotch Protein Latte, but it’s advertised as the Hopscotch Zero Sugar Added Protein Latte. The 16-ounce (0.5-liter) iced version has 7 grams of sugar and 11 grams of protein. By comparison, a 16-ounce (0.5-liter) iced Starbucks Sugar-Free Caramel Protein Latte has 9 grams of sugar and 29 grams of protein.

The lawsuit seeks damages on behalf of U.S. consumers who bought the drinks. It also wants the court to order Starbucks to stop using the label “sugar-free” on products that contain sugar.

—Dee-Ann Durbin, AP Business Writer

Associated Press

Warren Buffett says successful people get these 3 life decisions right

6 days 3 hours ago

Warren Buffett is incredibly wise—much wiser than I am. But beyond his impressive expertise in investments over the decades, the down-to-earth wisdom he shares publicly is not really that earth-shattering.

The reason is that Warren Buffett is saying it. He’s explaining, in the plainest terms, things our eighth-grade teacher might have told us, but because it’s coming from Buffett, it makes all the difference and millions listen.

Now 96, Buffett, who passed the CEO baton to Greg Abel but continues as chairman of Berkshire Hathaway, will always be remembered for useful advice that really hits home.

Here are three Buffett tips to help you go from dreaming to doing.

1. Don’t gamble what you have just to get something you don’t really need

Buffett once told grads at the University of Florida that he’s seen both businesses and people risk a lot—mostly out of greed—when they probably shouldn’t have.

Buffett said, “If you risk something that is important to you for something that is unimportant to you, it just doesn’t make sense. I don’t care if the odds you succeed are 99 to 1 or 1,000 to 1.”

2. Build connections with honest and ethical folks

He also encouraged the students to think of a classmate they believe has long-term potential, someone they’d want to receive 10 percent of their earnings for life.

“You would probably pick the one you responded the best to, the one who has the leadership qualities, the one who is able to get other people to carry out their interests,” said Buffett. “That would be the person who is generous, honest, and who gave credit to other people for their own ideas.”

3. Your life’s success can be summed up in one word: love

In the biography The Snowball: Warren Buffett and the Business of Life, Buffett explains that the highest measure of success in life comes from how many of the people you want to love you actually do love you.

Buffett points out that although some individuals die wealthy and have buildings named after them, “the truth is that nobody in the world loves them.” Ultimately, the true measure of how you’ve lived your life is based on love. “The more you give love away, the more you get,” said Buffett.

These three principles may sound simple, but living them consistently requires intention and discipline. And perhaps that’s Buffett’s larger lesson: A successful life isn’t built on knowing more. It’s built on making better choices about what—and who—matters most.

—Marcel Schwantes

This article originally appeared on Fast Company’s sister website, Inc.com. 

Inc. is the voice of the American entrepreneur. We inspire, inform, and document the most fascinating people in business: the risk-takers, the innovators, and the ultra-driven go-getters that represent the most dynamic force in the American economy.

Inc.

SpaceX stock is on the rise again: What’s behind the rocket and AI company’s October rally?

6 days 3 hours ago

Shares of SpaceX (Nasdaq: SPCX) are having a good October so far, reaching highs not seen since June, when Elon Musk’s space and AI company made its debut on the Nasdaq.

The stock rose over 18% in the last week, closing Monday at $171.09—higher than its IPO day close of $160.95 for the first time in three months. 

Overall, SpaceX hasn’t had the most successful time on the market, so why the sudden turnaround? 

It comes down to a few things. For starters, last week was promising for SpaceX, with the company launching multiple successful missions.

It was responsible for a crewed NASA mission to the International Space Station (ISS) and launching Google’s homegrown Tensor processing units into space, where the chips will orbit Earth in a capabilities test. 

Morgan Stanley’s vote of confidence

The next boost for SpaceX came on Sunday, courtesy of Morgan Stanley analyst Adam Jonas.

In a note about SpaceX’s stock, Jonas encouraged investors to take advantage of lower SpaceX share prices before the company reaches a few upcoming milestones, Yahoo Finance reports. 

Jonas explained: “We believe future AI product releases, Starship progress, and additional neocloud contracts showing continued pricing around $30-50/watt are all upside-skewed catalysts that can push the stock closer to our $300/share price target.” 

Musk-Trump relationship appears to be cooling off

On Monday, shares of SpaceX closed 7.63% up, growing by over 1.2% more during premarket trading on Tuesday. 

Notably, SpaceX CEO Elon Musk also seems to be back on better terms with his—for lack of a better word—frenemy, President Trump.

Last Wednesday, Musk was appointed a co-lead of Project Meridian, the government’s new initiative to understand the “future of warfare.” 

Then, on Sunday, Musk backed up Trump’s recent statement that super intelligence, or SI, sounds better than artificial intelligence. He told a commenter on X that SpaceXAI would be changing to SpaceXSI.

Sarah Fielding

Why America can’t build the iPhone

6 days 4 hours ago

For six decades, I’ve worked on product design and manufacturing for companies such as Polaroid, Seiko, and Apple, as well as startups. When I worked at Polaroid and Apple, they still had their own factories and chose to go to Asia to build products. As noted in Patrick McGee’s bestseller Apple in China, I was responsible for bringing Apple’s first product to Taiwan in 1994. As a product design engineer and program manager, I was always involved in where my products were manufactured, because of the impact manufacturing has on a product’s success.

In my jobs at Polaroid and Apple, I turned to Asia for different reasons. I brought manufacturing to Asia for Polaroid in the 1970s, when it was rarely done. By the time I did it at Apple in the 1990s, Apple was late to the game.

Today, as pressure mounts for Apple to build iPhones in the U.S., I know from all my experiences that it is an impossible demand. We don’t have the attitude, the infrastructure, or the resources. We lost that battle decades ago, and cannot will it back.

The U.S. never invested in building consumer tech manufacturing at the scale of China or Taiwan. We prioritized R&D, design, and innovation, and didn’t value low-margin manufacturing work. During the Cold War, U.S. government investment and incentives were directed toward aerospace and defense, not consumer electronics. Our manufacturing base became dominated by contractors focused on military specifications, not consumer mass production.

Manufacturing consumer electronic products, in contrast, requires an infrastructure of suppliers, competitive labor costs, large workforces, and flexibility. Resources in China and Taiwan have allowed many U.S. companies to dominate the world in technology. While China became the manufacturer to the world, it helped us become the innovators to the world.

Going offshore: the early days

When I joined Polaroid in 1966, I designed consumer cameras that sold millions per year. Once the design was done, we’d hand it off to our internal manufacturing group, only to have them come back to us months later with requests for small design tweaks to save a few cents here and there.

It was a slow, iterative process with little concern for time to market. I often wondered why I was working so hard to meet an aggressive design schedule and then had to wait around for the product to finally ship. Analysts and industry leaders emphasized the importance of time to market as a critical factor for a product’s success, especially in competitive and fast-evolving markets.

I wondered why we couldn’t be as creative in the rest of the process as we were in the design stages. So, I began to look for ways to get products to market more quickly.

Outsourcing manufacturing to companies building similar products seemed like a good approach. They already had the experience and knowledge, so they could move quickly. That allowed the manufacturing and design teams to collaborate earlier in the process.

It wasn’t that I didn’t try to do manufacturing in the United States. I reached out to companies with manufacturing capabilities that looked to be synergistic, but it often took weeks to hear back. Many of the companies were focused on defense-related products and showed little interest in building consumer tech products with tighter schedules and lower margins.

I wondered why this was the case. Could it be that these U.S. resources were focused on the defense industry during the Cold War and never invested in consumer manufacturing? Or perhaps the defense business was just more lucrative. It was disappointing, but, fortunately, I found another solution.

At Polaroid, I turned to a few companies in Japan that had been supplying some of our components and wanted a chance to build the entire product. They offered to take our design early in the process, improve it for manufacturing, and deliver the product in high volume much more quickly than we could on our own. We were being offered the opportunity to tap into their product expertise and quality-obsessed manufacturing that Japanese companies were known for, and to learn from them in the process.

It turned out that these companies were so good that we could almost drop off a drawing package and pick up the product months later. They brought speed, experience, and predictability, and enabled us to be much more effective designers with smaller teams. Every time I’d return from a visit to Japan, I’d feel a sense of accomplishment and excitement. It was like night and day compared with using our internal manufacturing organization.

This pattern repeated itself over the next few decades as I worked at other companies. When Japan became too costly and less efficient, I went to Taiwan and later China, as each of these countries developed their manufacturing capabilities.

The U.S. could have created similar capacity over the years, especially after the Cold War, but never did. Manufacturing was just never considered an important need. It was not glamorous and never considered to be strategic.

In the 1990s, when a company I cofounded, ThinkOutside, invented the Stowaway folding keyboard, we found a Taiwan keyboard company that was experienced with manufacturing tiny key mechanisms, and partnered with them. Like many other companies working to get products to market quickly, we were doing what we did best and letting others do what they did best.

At this time, there were a few contract manufacturers in the U.S., including Solectron and Flextronics, that could manufacture others’ products in their plants in the U.S. and elsewhere in the world. They started with printed circuit boards and had expanded into complete product manufacturing; they also had some design capabilities.

This evolution mirrored the tech industry’s growing reliance on outsourced manufacturing, driven by cost, scale, and time-to-market pressures. But I found that the U.S.-based options were bureaucratic lumbering giants, reminding me of my Polaroid manufacturing experiences. They wanted only to take on large-volume projects from well-established companies, and rarely took the kind of risks that Asian companies did.

Asia becomes the world’s manufacturer

Meanwhile, Taiwan and China were becoming destinations for companies to build technically complex products because they were so good at it. They were aided by huge government investments in office parks, infrastructure, and free-trade zones.

Taiwan quickly moved from building calculators in the 1970s to notebook computers in the 1980s. James Fallows chronicled the rise of China in his famous three-part 2007 article in The Atlantic, “China Makes, The World Takes,” as China became the manufacturer for the world.

Scores of Chinese companies became available to manufacture a customer’s original design. They were known as original equipment manufacturers, or OEMs. If they offered their own designs that a customer could sell under its name, they were called original design manufacturers, or ODMs.

It was a win-win partnership. We used China to build our products, and they relied on us keep their factories running by marketing and selling products they designed.

Companies often specialized in specific product categories. If you wanted to build a particular type of product, you’d go to a company that was already building something similar. You tapped into their expertise, supplier relationships, and buying power, and everyone would benefit from the economies of scale and relevant experience.

While some first-time customers worried about two competing products being made by the same OEM, each company’s areas were usually secured from the other. When I worked on the Barnes & Noble Nook e-reader, we used Foxconn, the same manufacturer that built the Amazon Kindle. That allowed us to go from an initial concept to market in less than a year.

Product designers large and small now had a destination where they could bring their product designs and get them manufactured quickly and efficiently. You no longer needed to be a Sony to have access to manufacturers. Chinese factories enabled thousands of companies across the United States and the world to turn their ideas into viable products.

As these OEMs and ODMs grew in number, component manufacturers and other suppliers opened their own factories nearby, close to the facilities using their parts, providing even greater efficiency and faster time to market.

As an example of how effective this was, I was about to ship the initial lot of a new consumer electronic product to the U.S. from Shenzhen, the Chinese technology hub adjacent to Hong Kong, and it was to arrive just before going on sale. At the last moment, I found an error in the instruction manual that needed to be fixed before the product could ship. We called the printer, which was a few blocks away. It made the correction, and delivered correctly printed manuals two hours later.

During this time, we never considered that we were taking jobs from Americans. Nothing like this ever existed in the U.S.—not the industry, the factories, nor the workers. What China offered was unique.

Apple was late to the game

When I joined Apple in 1994 to work on the Newton MessagePad personal digital assistant, the company was manufacturing most of its computers in its own factories in California, Colorado, Ireland, and Singapore, even though other computer companies had been outsourcing most of their notebooks to Taiwan for years.

The first version of Newton, the MessagePad 100, was developed with Sharp Electronics in Japan because of that company’s expertise in building handheld products such as its Wizard organizer. But its cost came in way above plan, and I was asked to quickly develop a new model at a more affordable cost.

Apple’s internal manufacturing organization had neither the interest nor experience to master products like the Newton. Its leaders considered our product to be a nuisance and encouraged us to find our own manufacturer.

Taiwan was the obvious answer. After all, that’s where Sharp was now building its second-generation Wizards, and where most of the world’s calculators and notebook computers were being built, other than Apple’s. The new Newton MessagePad 110 was the first time Apple developed a product to be manufactured in Taiwan.

I flew to Taipei and spent two weeks visiting potential manufacturers, mostly notebook and calculator manufacturers. We selected Inventec, a $320 million manufacturer at the time. It was busy producing calculators for Texas Instruments, phones and fax machines for telecom companies, and notebook computers for Compaq and Zenith.

But we ran into an immediate challenge. Inventec would need an $800,000 machine to assemble the processor chip powering the Newton, machinery not yet used in Taiwan. The company’s CEO, Richard Lee, insisted on buying it at Inventec’s expense. He never considered it a burden, explaining it would give them new capabilities.

Inventec assigned a group that began working with our Apple design team. We began with a handshake deal while Lee suggested we negotiate a contract in parallel. We all knew drawing up contracts could take many months, particularly at Apple, and he didn’t want to lose that time.

Our joint team of about a half-dozen engineers met monthly in Taipei. The industrial designer on the team, Jony Ive, had recently joined Apple. This would be one of his first projects, and his first time he’d been to Taiwan. (I later learned that he complained to his boss about how hard I made him work.)

The product was completed in eight months and went on to fail almost as badly as the first model. Sales volumes were about 10% of plan. A few months later when I apologized to Lee, he told me not be concerned. He was happy to be working with Apple and considered this to be a win. He was thinking of the long term, and was proud of the Apple relationship. I was embarrassed.

Inventec went on to develop and build notebook computers, servers, and a range of other products for most of the world’s technology companies, including Apple. Its revenues for 2025 were $22 billion.

How design impacts manufacturing

The Newton was constructed like most other consumer tech products at the time. It consisted of a molded plastic clamshell enclosure, a large printed circuit board populated with electrical components, a pressure sensitive touch screen, a stylus, and a battery compartment that held four AA cells. Ive’s design contribution was creating a beautiful fluid-looking package that made the product look smaller than it was. It was nicely done, but its fit and finish were not dissimilar from other products being produced at the time, such as Nokia phones. 

Years later, when Ive became Apple’s senior VP of industrial design, he elevated its design to a level never seen in consumer products. I recall seeing the first iPhone and marveling at how precisely the parts fit together, the flawless finishes of the parts, and the use of new materials never employed at mass scale.  His designs set a new standard for all consumer tech products. Other products suddenly seemed crude by comparison.

Apple’s design and manufacturing engineers were responsible for putting these new designs into mass production. It certainly could not be done in the U.S., which didn’t even have the ability to build much simpler products. The new design standards with the ultraprecise fit and finish meant that the products needed to be built China.

When I hear politicians demanding that iPhones be built in the U.S., it’s clear they have no understanding of how products are created and built. You can’t just wish it to happen. You would need to create much of what China and Taiwan have built over the past 30 years.

It’s not just setting up factory buildings filled with assembly machinery and workers. You would need the entire infrastructure of suppliers and manufacturers of the parts that go into the products: the factories to build displays, batteries, and electronic components. You’d require the experience, and the right attitude.

Shipping the components from China and doing final assembly in the U.S. would also cause huge issues. Let’s suppose you bring displays in from China, and they have a defect. If you were building the product in Shenzhen, you’d call the display company that’s an hour away and they would have engineers in your factory in a few hours to address the problem or provide new parts. Try that from the United States, and you would likely shut down your assembly line for several weeks.

Now consider what would happen once you multiply this by the thousands of parts and processes that go into a product. Not only is it inefficient, it’s also just not practical to build these products here. It makes as much sense as building an automobile in the Arctic from parts made in Detroit.

The Mac Mini isn’t an iPhone

With all this said, Apple, under pressure to bring products back to the U.S., has agreed to build Mac minis in Houston. They have asked Foxconn, the same company that has built, staffed, and managed much of Apple’s China manufacturing, to create and operate the assembly operation.

The Mac mini is a much simpler and lower volume product than the iPhone. Essentially, it’s a printed circuit board assembly housed in an aluminum box. But it will still require many of its components to be shipped from China. Politically, it may be a good move, but practically, it means very little.

It will be interesting to see if Apple’s new CEO, John Ternus, makes any fundamental changes to Tim Cook’s manufacturing strategy. As a product designer, I’m guessing that Ternus—who is also a product designer—wants to get his new products to market in the fastest and most efficient way possible and will continue to rely on Asia. That approach has helped make so many of his past products huge successes.

Phil Baker

Why America can’t build the iPhone

6 days 4 hours ago

For six decades, I’ve worked on product design and manufacturing for companies such as Polaroid, Seiko, and Apple, as well as startups. When I worked at Polaroid and Apple, they still had their own factories and chose to go to Asia to build products. As noted in Patrick McGee’s bestseller Apple in China, I was responsible for bringing Apple’s first product to Taiwan in 1994. As a product design engineer and program manager, I was always involved in where my products were manufactured, because of the impact manufacturing has on a product’s success.

In my jobs at Polaroid and Apple, I turned to Asia for different reasons. I brought manufacturing to Asia for Polaroid in the 1970s, when it was rarely done. By the time I did it at Apple in the 1990s, Apple was late to the game.

Today, as pressure mounts for Apple to build iPhones in the U.S., I know from all my experiences that it is an impossible demand. We don’t have the attitude, the infrastructure, or the resources. We lost that battle decades ago, and cannot will it back.

The U.S. never invested in building consumer tech manufacturing at the scale of China or Taiwan. We prioritized R&D, design, and innovation, and didn’t value low-margin manufacturing work. During the Cold War, U.S. government investment and incentives were directed toward aerospace and defense, not consumer electronics. Our manufacturing base became dominated by contractors focused on military specifications, not consumer mass production.

Manufacturing consumer electronic products, in contrast, requires an infrastructure of suppliers, competitive labor costs, large workforces, and flexibility. Resources in China and Taiwan have allowed many U.S. companies to dominate the world in technology. While China became the manufacturer to the world, it helped us become the innovators to the world.

Going offshore: the early days

When I joined Polaroid in 1966, I designed consumer cameras that sold millions per year. Once the design was done, we’d hand it off to our internal manufacturing group, only to have them come back to us months later with requests for small design tweaks to save a few cents here and there.

It was a slow, iterative process with little concern for time to market. I often wondered why I was working so hard to meet an aggressive design schedule and then had to wait around for the product to finally ship. Analysts and industry leaders emphasized the importance of time to market as a critical factor for a product’s success, especially in competitive and fast-evolving markets.

I wondered why we couldn’t be as creative in the rest of the process as we were in the design stages. So, I began to look for ways to get products to market more quickly.

Outsourcing manufacturing to companies building similar products seemed like a good approach. They already had the experience and knowledge, so they could move quickly. That allowed the manufacturing and design teams to collaborate earlier in the process.

It wasn’t that I didn’t try to do manufacturing in the United States. I reached out to companies with manufacturing capabilities that looked to be synergistic, but it often took weeks to hear back. Many of the companies were focused on defense-related products and showed little interest in building consumer tech products with tighter schedules and lower margins.

I wondered why this was the case. Could it be that these U.S. resources were focused on the defense industry during the Cold War and never invested in consumer manufacturing? Or perhaps the defense business was just more lucrative. It was disappointing, but, fortunately, I found another solution.

At Polaroid, I turned to a few companies in Japan that had been supplying some of our components and wanted a chance to build the entire product. They offered to take our design early in the process, improve it for manufacturing, and deliver the product in high volume much more quickly than we could on our own. We were being offered the opportunity to tap into their product expertise and quality-obsessed manufacturing that Japanese companies were known for, and to learn from them in the process.

It turned out that these companies were so good that we could almost drop off a drawing package and pick up the product months later. They brought speed, experience, and predictability, and enabled us to be much more effective designers with smaller teams. Every time I’d return from a visit to Japan, I’d feel a sense of accomplishment and excitement. It was like night and day compared with using our internal manufacturing organization.

This pattern repeated itself over the next few decades as I worked at other companies. When Japan became too costly and less efficient, I went to Taiwan and later China, as each of these countries developed their manufacturing capabilities.

The U.S. could have created similar capacity over the years, especially after the Cold War, but never did. Manufacturing was just never considered an important need. It was not glamorous and never considered to be strategic.

In the 1990s, when a company I cofounded, ThinkOutside, invented the Stowaway folding keyboard, we found a Taiwan keyboard company that was experienced with manufacturing tiny key mechanisms, and partnered with them. Like many other companies working to get products to market quickly, we were doing what we did best and letting others do what they did best.

At this time, there were a few contract manufacturers in the U.S., including Solectron and Flextronics, that could manufacture others’ products in their plants in the U.S. and elsewhere in the world. They started with printed circuit boards and had expanded into complete product manufacturing; they also had some design capabilities.

This evolution mirrored the tech industry’s growing reliance on outsourced manufacturing, driven by cost, scale, and time-to-market pressures. But I found that the U.S.-based options were bureaucratic lumbering giants, reminding me of my Polaroid manufacturing experiences. They wanted only to take on large-volume projects from well-established companies, and rarely took the kind of risks that Asian companies did.

Asia becomes the world’s manufacturer

Meanwhile, Taiwan and China were becoming destinations for companies to build technically complex products because they were so good at it. They were aided by huge government investments in office parks, infrastructure, and free-trade zones.

Taiwan quickly moved from building calculators in the 1970s to notebook computers in the 1980s. James Fallows chronicled the rise of China in his famous three-part 2007 article in The Atlantic, “China Makes, The World Takes,” as China became the manufacturer for the world.

Scores of Chinese companies became available to manufacture a customer’s original design. They were known as original equipment manufacturers, or OEMs. If they offered their own designs that a customer could sell under its name, they were called original design manufacturers, or ODMs.

It was a win-win partnership. We used China to build our products, and they relied on us keep their factories running by marketing and selling products they designed.

Companies often specialized in specific product categories. If you wanted to build a particular type of product, you’d go to a company that was already building something similar. You tapped into their expertise, supplier relationships, and buying power, and everyone would benefit from the economies of scale and relevant experience.

While some first-time customers worried about two competing products being made by the same OEM, each company’s areas were usually secured from the other. When I worked on the Barnes & Noble Nook e-reader, we used Foxconn, the same manufacturer that built the Amazon Kindle. That allowed us to go from an initial concept to market in less than a year.

Product designers large and small now had a destination where they could bring their product designs and get them manufactured quickly and efficiently. You no longer needed to be a Sony to have access to manufacturers. Chinese factories enabled thousands of companies across the United States and the world to turn their ideas into viable products.

As these OEMs and ODMs grew in number, component manufacturers and other suppliers opened their own factories nearby, close to the facilities using their parts, providing even greater efficiency and faster time to market.

As an example of how effective this was, I was about to ship the initial lot of a new consumer electronic product to the U.S. from Shenzhen, the Chinese technology hub adjacent to Hong Kong, and it was to arrive just before going on sale. At the last moment, I found an error in the instruction manual that needed to be fixed before the product could ship. We called the printer, which was a few blocks away. It made the correction, and delivered correctly printed manuals two hours later.

During this time, we never considered that we were taking jobs from Americans. Nothing like this ever existed in the U.S.—not the industry, the factories, nor the workers. What China offered was unique.

Apple was late to the game

When I joined Apple in 1994 to work on the Newton MessagePad personal digital assistant, the company was manufacturing most of its computers in its own factories in California, Colorado, Ireland, and Singapore, even though other computer companies had been outsourcing most of their notebooks to Taiwan for years.

The first version of Newton, the MessagePad 100, was developed with Sharp Electronics in Japan because of that company’s expertise in building handheld products such as its Wizard organizer. But its cost came in way above plan, and I was asked to quickly develop a new model at a more affordable cost.

Apple’s internal manufacturing organization had neither the interest nor experience to master products like the Newton. Its leaders considered our product to be a nuisance and encouraged us to find our own manufacturer.

Taiwan was the obvious answer. After all, that’s where Sharp was now building its second-generation Wizards, and where most of the world’s calculators and notebook computers were being built, other than Apple’s. The new Newton MessagePad 110 was the first time Apple developed a product to be manufactured in Taiwan.

I flew to Taipei and spent two weeks visiting potential manufacturers, mostly notebook and calculator manufacturers. We selected Inventec, a $320 million manufacturer at the time. It was busy producing calculators for Texas Instruments, phones and fax machines for telecom companies, and notebook computers for Compaq and Zenith.

But we ran into an immediate challenge. Inventec would need an $800,000 machine to assemble the processor chip powering the Newton, machinery not yet used in Taiwan. The company’s CEO, Richard Lee, insisted on buying it at Inventec’s expense. He never considered it a burden, explaining it would give them new capabilities.

Inventec assigned a group that began working with our Apple design team. We began with a handshake deal while Lee suggested we negotiate a contract in parallel. We all knew drawing up contracts could take many months, particularly at Apple, and he didn’t want to lose that time.

Our joint team of about a half-dozen engineers met monthly in Taipei. The industrial designer on the team, Jony Ive, had recently joined Apple. This would be one of his first projects, and his first time he’d been to Taiwan. (I later learned that he complained to his boss about how hard I made him work.)

The product was completed in eight months and went on to fail almost as badly as the first model. Sales volumes were about 10% of plan. A few months later when I apologized to Lee, he told me not be concerned. He was happy to be working with Apple and considered this to be a win. He was thinking of the long term, and was proud of the Apple relationship. I was embarrassed.

Inventec went on to develop and build notebook computers, servers, and a range of other products for most of the world’s technology companies, including Apple. Its revenues for 2025 were $22 billion.

How design impacts manufacturing

The Newton was constructed like most other consumer tech products at the time. It consisted of a molded plastic clamshell enclosure, a large printed circuit board populated with electrical components, a pressure sensitive touch screen, a stylus, and a battery compartment that held four AA cells. Ive’s design contribution was creating a beautiful fluid-looking package that made the product look smaller than it was. It was nicely done, but its fit and finish were not dissimilar from other products being produced at the time, such as Nokia phones. 

Years later, when Ive became Apple’s senior VP of industrial design, he elevated its design to a level never seen in consumer products. I recall seeing the first iPhone and marveling at how precisely the parts fit together, the flawless finishes of the parts, and the use of new materials never employed at mass scale.  His designs set a new standard for all consumer tech products. Other products suddenly seemed crude by comparison.

Apple’s design and manufacturing engineers were responsible for putting these new designs into mass production. It certainly could not be done in the U.S., which didn’t even have the ability to build much simpler products. The new design standards with the ultraprecise fit and finish meant that the products needed to be built China.

When I hear politicians demanding that iPhones be built in the U.S., it’s clear they have no understanding of how products are created and built. You can’t just wish it to happen. You would need to create much of what China and Taiwan have built over the past 30 years.

It’s not just setting up factory buildings filled with assembly machinery and workers. You would need the entire infrastructure of suppliers and manufacturers of the parts that go into the products: the factories to build displays, batteries, and electronic components. You’d require the experience, and the right attitude.

Shipping the components from China and doing final assembly in the U.S. would also cause huge issues. Let’s suppose you bring displays in from China, and they have a defect. If you were building the product in Shenzhen, you’d call the display company that’s an hour away and they would have engineers in your factory in a few hours to address the problem or provide new parts. Try that from the United States, and you would likely shut down your assembly line for several weeks.

Now consider what would happen once you multiply this by the thousands of parts and processes that go into a product. Not only is it inefficient, it’s also just not practical to build these products here. It makes as much sense as building an automobile in the Arctic from parts made in Detroit.

The Mac Mini isn’t an iPhone

With all this said, Apple, under pressure to bring products back to the U.S., has agreed to build Mac minis in Houston. They have asked Foxconn, the same company that has built, staffed, and managed much of Apple’s China manufacturing, to create and operate the assembly operation.

The Mac mini is a much simpler and lower volume product than the iPhone. Essentially, it’s a printed circuit board assembly housed in an aluminum box. But it will still require many of its components to be shipped from China. Politically, it may be a good move, but practically, it means very little.

It will be interesting to see if Apple’s new CEO, John Ternus, makes any fundamental changes to Tim Cook’s manufacturing strategy. As a product designer, I’m guessing that Ternus—who is also a product designer—wants to get his new products to market in the fastest and most efficient way possible and will continue to rely on Asia. That approach has helped make so many of his past products huge successes.

Phil Baker

Consumer brands are digital health’s missing link

6 days 4 hours ago

At the EWA, we enable C-suite women to mentor each other to achieve personal and professional success. I am honored to share insights from thought leaders who are part of our peer-to-peer community.

This month I introduce Annie Bloomquist, a consumer and digital health executive who has spent her career at the intersection of consumer trust and emerging technology. She led transformations across retail, consumer products, and digital health. She serves on the board of a private equity-backed medical device company and advises growth-stage companies on strategy, commercial execution, and scaling.

Segil: Consumers are buying health and wellness technology in record numbers, yet research shows only a fraction achieving their wellness goals. What’s the gap, and who is responsible for closing it?

Bloomquist: Eighty-four percent of consumers in the U.S. say wellness is their priority. Consumers are wearing their devices and downloading apps. What is failing is the sustained connection that converts intention into behavior change over time. The technology has to work by being effortless, ambient, and acting on behalf of the consumer rather than demanding attention from them. Technology alone does not sustain a relationship. The industry has underinvested in the longitudinal trust that makes a consumer keep going when motivation fades. The tools and data exist. What has been missing is the relationship consumer brands are built to provide.

Segil: You state the most valuable asset a consumer brand brings to health is not its product.

Bloomquist: Yes, the most valuable asset is the relationship. It’s the longitudinal trust accumulated over years of daily life, and the data that trust makes possible. Consumers who believe in a brand share more honestly, longer. That’s what turns a consumer dataset into a scientific asset. What clinical health platforms cannot easily replicate is that earned relationship. The ones who get it right treat the consumer relationship as infrastructure and build the health platform on top of it.

Segil: You have led this kind of transformation from the inside. What didn’t you appreciate until you were in it?

Bloomquist: It is difficult to hold two business models simultaneously. Either the legacy business wins and the platform never gets the resources it needs, or leadership moves too fast and breaks the foundation that is paying for the future. What holds both together is a leadership team that can make the case for both simultaneously.

The patience requirement is different for clinical and scientific partnerships versus commercial ones. It is built over years, not quarters.

Realizing the consumer has begun to trust you with something far more intimate than you asked for is not a problem. It is the most significant obligation the work creates.

Segil: Consumer brands are accustomed to partnerships with defined short-cycle commercial returns. How does that logic change when health outcomes are the goal?

Bloomquist: The companies that skip third-party scientific validation, treating it as a marketing expense rather than a foundational investment, will eventually face a credibility ceiling.

Partnerships with health systems, research institutions, and clinical bodies operate on longer cycles and require patient capital. The leaders who get this right treat these relationships as an extension of research and development, not a marketing partnership. They staff and protect them accordingly. Third-party validation converts a skeptical consumer into an engaged one and a skeptical health system into an advocacy channel. It is a flywheel.

Segil: The lines between consumer brands and digital health platforms are blurring. What does that mean for how leaders should think about market opportunity?

Bloomquist: The important question is not what share of an existing market a brand can capture. It’s what becomes accessible as consumer and digital health sectors continue to converge. Consumers increasingly expect health outcomes from the brands they already trust, and health platforms increasingly need the engagement infrastructure that consumer brands have spent decades building.

AI accelerates everything in this space, widening the gap between platforms that have earned longitudinal consumer data. It is the data infrastructure AI needs. A platform trained on years of continuous consumer engagement will outperform one trained on episodic clinical encounters.

The ones who get it right define the business by what it enables, not what it sells.

Segil: What’s your message to the consumer brand executive or board who see this opportunity but hasn’t yet committed to it?

Bloomquist: The window is real. Consumer brands bring something that digitally native health platforms are spending years trying to build: an existing relationship and longitudinal behavioral data. The brands that move with intention now, building clinical credibility and staffing for the right leadership, will define the next decade of health outcomes at scale. The ones that wait will find the consumer trust advantage competed away by digitally native health brands that are learning the consumer relationship faster than most incumbents expect.

Larraine Segil is founder, chair, and CEO of the Exceptional Women Alliance.

Larraine Segil

Robots are going to need a better story

6 days 4 hours ago

In 1897, Georges Méliès made Gugusse et l’Automate, one of the earliest films to feature a robot. The machine grows, fights its maker, and is eventually destroyed. It set the tone.

For much of the next 120 years, our impressions of robots came from the silver screen. From the terrifying liquid-metal T-1000 in Terminator 2 to the murderous NS-5s in I, Robot, we have repeatedly imagined that the machines we invent will eventually turn on us.

Of course, for every evil machine, there’s a WALL-E or C-3PO. But hostile robots scare us. Negativity bias makes our minds naturally give disproportionate attention to threats, loss, and things beyond our control. Popular culture didn’t invent our fear of machines, but it has had more than a century to compound it. Until recently, those fears could remain safely within our imaginations.

THE ROBOTS ARE HERE

In recent years, investment in robotics and “physical AI” has surged at a record pace, with global funding growing from about $4 billion in 2019 to $26 billion in 2025. China is pushing humanoid robots from demonstrations into factories, with Morgan Stanley projecting that annual Chinese shipments could reach 446,000 by 2030.

But it’s important to acknowledge that robots don’t always have two arms and two legs or look like us. Many have been working alongside us for decades. They arrived in automotive factories in the 1960s and, by the 1980s, were considered a core production technology. We’ve happily watched robot vacuum cleaners make their way around our homes for years. But a giant arm endlessly spot-welding a car, or two brushes cleaning dog hair from the floor, feels very different from a machine that looks and behaves like us. So we find ourselves at a juncture: Our definition of a robot needs to broaden, just as the ones that do look like us are suddenly becoming much more visible.

FROM CIRCUS ACT TO EMPLOYEE

For years, Boston Dynamics has entertained the internet with bipedal robots running, jumping, and doing backflips. But at CES this year, the backflips stopped and the company unveiled the production version of Atlas. The emphasis was now on work: handling parts, changing its own battery, and operating autonomously in industrial environments.

And we’re feeling this outside of work, too. In late 2025, robotics company 1X opened preorders for NEO, its humanoid home robot, for $20,000 or $499 a month. Its soft exterior, light weight, and deliberately domestic design are a long way from science fiction’s metal machines. It is all packaged up on an unassuming, familiar website.

The brands producing robots must move beyond the future invention story to everyday use. That starts with where these robots live.

OUR HOMES ARE DIFFERENT

In industrial settings, adoption will largely become an economic decision. Once capabilities, reliability, servicing, and costs align, companies will use robots of all types, regardless of unemployment fears. The economic case will overcome societal challenges, especially for high-frequency, mundane tasks, while delivering significant productivity uplifts. Storytelling and good branding will still be essential, but the blockers are easily overcome.

But a machine that enters our home, handles our possessions, or helps care for us has to cross an emotional threshold. For most people, the robot’s capabilities will not be enough. We will have to accept and trust it. That creates an extraordinary and novel challenge for new brands building around robotics.

The industry naturally wants to wow us with what its machines can do. But every demonstration of something recognizably human can reinforce fears following robots for a century: Look what it can do instead of you.

The distance between home and work is wide, but what about a third space? You already see robots cleaning in transport hubs and bussing dishes in large hospitality settings. This is the opportunity for these new brands. In spaces we occupy but don’t own, the value can be demonstrated through robots’ abilities to improve our experiences and environments. Brands might have to straddle a B2B2C situation, but showing how a robot can improve that space may make us more open to letting one into a space we own.

An elderly parent looked after by a robot sounds dystopian when the imagined alternative is a caring human. It’s fraught with guilt. But across aging societies struggling with care shortages, that alternative will not always be available. With population sizes decreasing, the choice may be between robot-assisted care and not enough care. But before we get there—and before our imaginations run wild again—there is more of the robot story still to be told.

HERE TO HELP

Robotics isn’t simply a story about replacement or revolution. It’s about us building a very different relationship with this technology—an emotional one, focused on making things better. We will likely eventually name our robots. This is already happening: The cleaning robot in my London train station is called Scrubsy.

We’re looking at perhaps the first mass-market technology we don’t operate. We need to trust what robots do, what they see, their decisions, and ultimately, the companies standing behind them. I can’t think of a bigger—or, to be honest, more exciting—branding challenge today. In Terminator 2, Cyberdyne Systems builds Skynet. It gives robot brands a case study in the opposite kind of brand they need to build: a nemesis, of sorts.

Robot companies of all sizes and scales will need to balance invention with use. They will need to address concerns head-on, with effective storytelling and films that show and explain. The recent AI boom has brought a raft of excellent advertisements showing how and why an LLM can be a powerful presence in our lives—one we shouldn’t be scared of. Robots will be no different from AI in this regard, but their brands need to go even further.

We are getting remarkably good at building machines that can behave like us. The challenge will be telling their story in a way that makes us want to let them in.

James Greenfield is CEO and cofounder of Koto.

James Greenfield

A new back-to-school focus on non-traditional learners

6 days 4 hours ago

As millions of students head back to campus this fall, colleges and universities are rightly focused on incoming freshmen, enrollment numbers, and retention rates. But there is another population that deserves attention: the more than 37 million Americans under age 65 who have some college credits but no degree. At a time when we need more skilled people in the workforce, these 37 million are one of the largest untapped talent pools for U.S. employers.

Many of these adults don’t fit the traditional student mold. They are parents, frontline workers, veterans, caregivers, and professionals already building careers. They have demonstrated their willingness to pursue higher education and were enrolled at some point, but life got in the way.

A recent brief from Pearson and the American Council on Education, Reengaging Stopped-Out Learners: Institutional Strategies for Return and Completion, highlights why learners “stop out” and what motivates them to return. Financial pressures, competing responsibilities, and concerns about readiness often interrupt educational journeys. Yet career advancement, personal fulfillment, and family aspirations remain powerful drivers for reengagement.

LEARNER-CENTERED EDUCATION

The challenge for higher education is clear: If we want these learners back, we cannot expect them to return to the same systems that did not accommodate their realities in the first place.

For decades, much of higher education has been designed around the needs of full-time, campus-based students. But stopped-out learners require a different approach. They need flexible pathways that acknowledge work schedules, caregiving responsibilities, and credits for prior learning experiences. They need educational models that fit into their lives instead of requiring them to press pause on everything else.

Fortunately, many institutions are already beginning to rethink what learner-centered education looks like. Three main areas where colleges can make meaningful progress include flexible program delivery, stronger data infrastructure, and expanded recognition of prior learning, work experience, and military training.

These recommendations represent a fundamental shift in how we think about student success.

Imagine a working professional who left college eight years ago after completing most of a business degree. Today, that individual may have accumulated significant workplace experience, completed employer training programs, and developed in-demand technical skills. Asking them to start over makes little sense. Instead, institutions should find innovative ways to recognize demonstrated competencies, accelerate degree completion, and connect learning directly to career outcomes.


NATIONAL SKILLS CHALLENGE

Technology also has an important role to play. Advances in digital learning, artificial intelligence, and personalized education can make higher education more responsive. Learning experiences can now adapt to individual needs. They can provide support on demand and help students progress at a pace that works for them. The future of higher education will be defined by how effectively it helps people achieve meaningful outcomes.

This matters far beyond the campus.

America faces a growing skills challenge. Employers across industries are searching for talent. At the same time, millions of adults already possess partial college experience and valuable workplace knowledge, but lack the degree credential that can unlock new opportunities. Reengaging stopped-out learners offers one of the fastest and most effective ways to strengthen the workforce while improving economic mobility.

LIFELONG LEARNING

Back-to-school season should remind us that education is not confined to an 18-to-22-year-old experience. Learning is lifelong. The next generation of higher education leaders will understand that learners move in and out of education throughout their lives and design systems accordingly.

The opportunity is enormous. Millions of Americans have already taken the first step by enrolling in college. This fall, higher education should consider what it would take to help them finish.

The answer may enrich the lives of millions of people and drive the future of our workforce and economy.

Tom ap Simon is president of higher education and virtual learning at Pearson.

Tom Ap Simon

People will be your competitive advantage

6 days 4 hours ago

One of the biggest mistakes companies are making with AI is treating it primarily as a way to reduce talent, rather than as an opportunity to rethink how people and technology can work together.

The temptation is understandable, as AI can automate work and take on tasks that once required large teams. Increasingly, HR has become an obvious place to focus on staffing reductions. AI can screen candidates, answer employee questions, and analyze workforce data.

This results in leaders asking how many HR staff members they still need. The bigger opportunity, though, is to design the organization to succeed in the future. In the AI age, one of the greatest competitive advantages may be something distinctly human: your people strategy.

PEOPLE STRATEGY IS BUSINESS STRATEGY

I was once talking with Steve Kerr, coach of the Golden State Warriors, about people strategy. He told me that one of the most important values he instills in his team is connection.

Every player walks onto the court with something different happening in his life. One may be under enormous pressure to perform. Another may be dealing with something personal. Someone else may not be having his best day. Yet when the game begins, they have to figure out how to work together. If that connection breaks down, the entire team strategy can break down with it.

Companies are no different.

You can hire extraordinary people. Invest in the best technology. Build a smart business plan. But none of it guarantees that people will come together in a way that delivers the outcomes you want.

That is where people strategy comes in. It connects the business model to how people operate every day, from culture and organizational structure to decision-making, leadership behaviors, and processes, to make it happen.

The strongest CEOs understand that people strategy begins at the top. They work with their leadership team and people leaders to determine how the organization needs to operate to achieve its goals.

EVERY CEO NEEDS A PEOPLE STRATEGIST

People strategy is a leadership responsibility. The CEO needs a trusted partner who brings a deep understanding of people and organizations to the table, helping translate business priorities into the talent, culture, structure, and ways of working required to achieve outcomes. I call that person a people strategist.

A people strategist is not someone who just understands compensation, recruiting, benefits, or employee relations. While important, a great people strategist also understands the business and serves as a strategic partner to the CEO and leadership team.

They know how the company makes money. They understand the strategy. They can connect what is happening across finance, technology, operations, sales, and people. They see where the organization is getting stuck and understand how changes in talent and technology, as well as structure and culture. They can also help devise ways of working to help move it forward.

I often say that the best people strategists are business people, where people are their product.

STOP DESIGNING AROUND YOUR CURRENT ORGANIZATION

Another challenge I often see is that companies are trying to evolve the organization they already have.

They look at their current jobs and ask which tasks AI can automate. They look at employees and ask what new skills they need. They look at existing structures and try to make them more efficient. 

A better starting point is thinking about the problem we are trying to solve. What are we trying to accomplish? What value are we trying to create? What should a person do versus what technology should do? Where does combining the two produce something better?

Then design the work from there. That may result in very different organizations. We may rely less on static job descriptions and more on teams organized around specific problems. Companies may use a combination of full-time employees, independent experts, consultants, partners, and technology depending on what needs to be accomplished.

The point is to stop assuming the organization has to look like the one we have today.

We made a similar mistake during the pandemic. Many companies moved employees from an office to their homes and considered that a transformation. They changed the where, but not necessarily the how.

AI gives us another opportunity to redesign how work happens. We should not waste it by layering new technology onto old ways of working. The companies that get this right will build a better organization combining the best resources.

PEOPLE ARE THE DIFFERENTIATOR

As AI becomes more powerful and widely available, companies will increasingly have access to many of the same tools. The technology itself will not be enough to create an advantage. The difference will be what people do with it.

People bring judgment, curiosity, creativity, relationships, and context. They see connections others may not see. They understand when to follow the data and when to question it. And they combine ideas and technology, along with experience, in ways that can create something new.

As technology becomes more ubiquitous, people will become an even greater source of differentiation. The companies that succeed will have the strongest people strategies. They will know how to bring together the right talent, leadership, culture, and technology to achieve what others cannot.

Tami Rosen is a board member, advisor, and executive at finance and technology companies.

Tami Rosen

National Taco Day freebies, deals, and specials for 2026: Where to score big on the ultimate Taco Tuesday

6 days 4 hours ago

When you are having a hard workday, it is comforting to remember that tacos fall apart and people still love them.

This metaphor is particularly timely on National Taco Day, which just so happens to be today (Tuesday, October 6, 2026). Regardless of your emotional state, tacos are always a good idea.

Here’s some history and where to score some deliciousness.

A brief history of the taco

Let’s talk about tacos. The stuffed hand-held tortilla dish we know today evolved from Native and Mexican culinary traditions, though the exact details are unknown.

Many, such as the historian Jeffrey M. Pilcher, believe the moniker itself can be traced to 18th-century silver mines in Mexico. Miners would wrap gunpowder in paper and place it in the rocks as part of the excavation process, and call them tacos.

They also consumed street food versions that became known as tacos de minero.

As industrialization brought workers and their families to Mexico City, culinary fusion took place.

One of the first times tacos are mentioned in the United States is in a 1905 newspaper. Mexican immigrants were working in America on the railroads and mines and brought their favorite dishes from home with them.

In Los Angeles, tamales were sold on pushcarts. In San Antonio, women known as the Chili Queens sold Mexican food such as tacos around the Alamo.

As the children of Mexican immigrants grew up in the United States, they continued to eat foods from their parents’ homeland, including tacos.

Families began incorporating ingredients that were readily available in America, such as cheddar cheese, iceberg lettuce, and hamburger meat.

Today, the taco is a staple in American cuisine. Its versatility allows the consumer to customize it according to their stomach’s delights.

National Taco Day freebies and deals

Now that you are an informed connoisseur of tacos, let’s dive into the deals.

Margaritas Mexican Restaurant

Margaritas Mexican Restaurant loves tacos so much that it is celebrating all month long. October is now “Tacotoberfest.” For the whole month, rewards members can get 100 extra bonus points when ordering tacos during happy hour.

On National Taco Day, those same rewards members who dine in can get a free taco with purchase.

If you are feeling extremely hungry and competitive, beginning on National Taco Day through the end of the month, you can take part in the Taco Gigante Challenge for the chance to win prizes. All you have to do is work your way through a two-pound taco.

Del Taco

Del Taco also celebrates Tacotoberfest. Rewards members can get a free taco with any purchase on the big day and rotating buy-one, get-one-free offers the rest of the month.

Chuy’s

Do you love dress-up? Do you love Chuy’s? Then we have a deal for you. On National Taco Day, don your best taco costume, snap a picture, and share to social media with the hashtag #ChuysTacoDay.

You will be rewarded with a free entrée. If dress-up isn’t your thing, you can simply add a crispy or soft ground beef taco to your entrée for $1. Additionally, you can add a floater shot of tequila or rum to any margarita for just $1. Taco eating can make you pretty thirsty.

Fuzzy’s Taco Shops

At participating Fuzzy’s Taco Shops, celebrate National Taco Day by ordering $2 original tacos. Customers will also be given a scratch-off card that comes with a guaranteed prize for a future visit. The prize possibilities include options such as free chips and queso or even free tacos for a year.

Kroger

If you are wanting to stay in and cook at home this National Taco Day, Kroger has you covered.

Log in to your Kroger account online or in the Kroger app. Add items such as Kroger Brand Ground Beef, Mexican Style Blend Shredded Cheese, Simple Truth Organic Yellow Corn Taco Shells, and Seasoned Black Beans to your cart.

Make sure to clip and redeem the current coupon good for $20 off your first online order of $75 or more. This deal runs through October 6.

Laredo Taco Company

Laredo Taco Company restaurants located inside 7-Eleven, Speedway, and Stripes stores are having an all-day taco celebration for the big occasion.

Breakfast-themed options include the buy-one, get-one free potato-and-egg tacos, two-for-$5 El Gran Tocino tacos, or a $5 El Gran Tocino burrito.

For lunch or dinner, consider the buy-one, get-one free chicken fajita taco or the $5 taco meal deal. The latter comes with chicken and bean-and-cheese tacos, a small side and Big Gulp drink.

Moe’s Southwest Grill

National Taco Day is three times the fun at Moe’s Southwest Grill. There you can order up to three $2 tacos. The deal is extended through October 11 if you are a loyalty member.

No matter how you feel and where you celebrate, we hope your National Taco Day guacs.

Shannon Cudd

The 3 next big things from midsize companies for 2026

6 days 5 hours ago

The continued growth of AI is streamlining tasks, such as event planning, that once required tabbing between spreadsheets, emails, and vendor websites. It’s also unleashing new possibilities for innovations that can tackle its need for reliable and affordable energy. These companies, employing between 100 and 499 people, are taking advantage of both types of AI opportunities.

BoomPop
For making corporate event planning less of a headache
Corporate events are a $1.5 trillion market, but actually planning them has historically left companies downing in a sea of disparate apps. BoomPop has created an AI-native platform that can find locations for events from corporate retreats to customer dinners, gather rates and quotes, and enable booking with just a few clicks. The platform, which relies on a proprietary database of roughly 1.5 million vendors, can also craft invitations, track RSVPs, and integrate with calendar software. The company has booked more than $60 million in business for venues in the past two years, assisting clients such as Google, Netflix, Amazon, and Dick’s Sporting Goods.

Lightmatter
For using light to connect the chips that power AI
Modern AI models rely on small neural networks called “experts” that are focused on different types of problems and are typically spread across hundreds of GPU chips in a data center. These chips need to share data, but electrical connections, and even traditional optical networks, aren’t fast enough to shuffle information at the speed required. Lightmatter’s Passage networking system, powered by microscopic lasers, delivers speedy connections that let models train up to three times faster and deliver results up to 11 times faster while using a fraction of previous power requirements. In March 2026, Lightmatter and Qualcomm announced they had achieved a record-breaking 1.6 Tbps bandwidth per fiber. The company has launched an open standards initiative within the Open Compute Project aimed at setting standards for integrating fiber connections with computing chips.

Torus
For helping the electrical system run smoothly even as loads rapidly shift
Torus builds electrical storage systems that can help boost grid capacity and more smoothly address sudden shifts in demand. Using a mix of the company’s Torus Spin fast-responding mechanical flywheel systems and battery storage, its Torus Station technology can respond in milliseconds to the needs of the grid without degrading over time like pure battery systems. An AI orchestration platform called Torus Overwatch anticipates peaks and handles preventive maintenance, while built-in cybersecurity technology keeps the system shielded from hackers. In 2025, Torus helped utilities respond to more than 360 real-world demand response events, opened a 545,000-square-foot manufacturing facility in Salt Lake City, and announced $200 million funding from asset manager Magnetar.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Steven Melendez

The 5 next big things in media and entertainment for 2026

6 days 5 hours ago

The next big things in media and entertainment remove friction for both creators and consumers. From deploying AI to handle the tedious aspects of animation to leveraging new technology to make the experience of viewing sports more dynamic, these innovations handle the busywork so humans can focus on the good stuff.

Autodesk
For empowering animators to spend more time on creative work
MotionMaker, a new feature in Autodesk’s Maya animation software, uses an autoregressive motion generation model to predict character movement. As a result, animators can spend less time on repetitive production tasks and more time on iteration and refinement. The technology makes animation more like directing a digital actor than manually piecing together movement frame by frame.

L-Acoustics
For making massive venues sound small
L1, the latest sound system from French professional audio company L-Acoustics, debuted at the Hollywood Bowl in May 2026. It does more with less when powering concerts in large venues, using software-steered sound to deliver consistent, studio-quality audio. A compact L1 column delivers the power of a traditional speaker stack up to three times its size, meaning fewer blocked sight lines and thus fewer “bad seats.”

Lemonlight
For streamlining video production
Lemonlight’s Hero is AI that’s clearly built by video production insiders. The technology enables production teams to storyboard, generate shot lists and call sheets directly from scripts, and apply varying levels of creative control. Directors can fine-tune every detail, or move from concept to production with a single click. The result is not just faster video, it’s better video. 

Linguana
For giving global scale to creator partnerships
For brands, the fundamental issue with influencer partnerships is that they don’t scale. Linguana changes that equation. The AI-powered platform lets brands run a single campaign that can be seamlessly integrated into creator content across languages and markets. The tech also works for creators, allowing them to expand their reach without being limited by their native language or geography. 

Peripheral
For bringing spatial intelligence to all levels of sport
Peripheral’s neural rendering systems deliver broadcast-quality 3D reconstructions of sporting events at one-tenth the cost of previous products. The technology gives broadcasters access to storytelling formats that traditional camera tech cannot produce, offering Gen Z and Alpha fans the any-angle replays they’re familiar with from gaming. It became part of the NBA’s Launchpad program in January 2026, quickly leading to pilot deployments with NBA-affiliated teams.

Utopai Studios
For solving the problem of narrative continuity in AI
Because Utopai is, at its core, a film studio, it has firsthand knowledge of the needs directors are looking to address with AI. The company’s PAI video generator supports up to three continuous minutes of 4K video generation with a single narrative flow, and it can maintain character consistency across different shots and environments. Directors and creatives can use PAI on its own or as part of broader creative workflows. The product hit $11 million in annual recurring revenue within six weeks of its release.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Maia McCann

The 3 next big things in global innovation for 2026

6 days 5 hours ago

While U.S. companies continue to dominate global news, these companies are solving problems abroad. The three honorees, from diverse industries, are addressing specific challenges in the markets they serve: reducing drag on boats, helping ranchers manage livestock, and improving customer interactions. Each company is applying new technology to a practical problem in the market where it operates.

Halter
For giving ranchers a high-tech solution to manage their livestock
Livestock ranching has traditionally relied on labor-intensive work. Halter is making it easier for ranchers to manage livestock, helping them track elements like grazing systems and herd movement while relying less on physical infrastructure. This is especially important as the effects of climate change increase and ranchers need to develop solutions for more sustainable food production.

Synthesia
For using AI to improve customer interactions
Synthesia makes AI avatars that help employees practice interactions, including role-play scenarios like handling issues during sales calls. Employees then receive feedback, while the software tracks their skills progression. A USC study found AI avatars statistically equivalent to human presenters in terms of message impact. The company raised a $200 million Series E at a $4 billion valuation.

Vessev
For creating technology that reduces drag on boats
Vessev makes electric boats that move people across the water more efficiently by adding carbon-fiber underwater wings called hydrofoils, which lift the hull above the water as the boat moves, cutting down on drag. The company’s technology is used by ferries and in the tourism industry to give riders a more comfortable alternative to typical passenger boats.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Yasmin Gagne

The 7 next big things in health and medicine for 2026

6 days 5 hours ago

As these honorees show, the future of medicine is looking more and more . . . futuristic. They include AI that diagnoses more than a dozen serious conditions from a single abdominal scan, a sci-fi-worthy clinic that reimagines the preventive care model, and a psychedelic that tackles treatment-resistant depression with a synthetic version of a Sonoran Desert toad secretion. Need help with paying rising out-of-pocket medical costs? There’s even a solution for that.

Aidoc
For massively streamlining the interpretation of medical imaging 
Roughly one in four adults will need medical imaging this year, creating a daunting caseload for radiologists who interpret the scans. AI can help, but most tools assess single conditions, resulting in diagnostic blind spots and critical care delays. Aidoc’s operating system for clinical radiology, called aiOS, consolidates these separate workflows. In January 2026, the FDA cleared Aidoc’s comprehensive abdomen CT triage tool, which can diagnose 15 acute conditions—including appendicitis, aortic dissection, and bowel obstruction—from a single scan. With a total of 30-plus FDA-cleared algorithms to date—spanning cardiology, oncology, and vascular conditions—Aidoc has analyzed more than 120 million patient cases at over 1,600 hospitals and raised more than $500 million to date. In August, the company announced the creation of the Diagnostic AI Consortium, in which a dozen of the largest hospitals and health systems in the U.S. will develop standards for AI usage in clinical decision-making. 

Akido
For expanding healthcare capacity through improved teamwork 
Akido‘s ScopeAI clinical automation platform expands the effectiveness of  multidisciplinary care teams by enabling nonmedically trained outreach workers to begin patient intake and diagnosis before a doctor is available. Trained on more than 10 million real-world clinical encounters, it listens to patient interviews on a tablet or laptop and suggests follow-up questions. An initial diagnosis and treatment plan is then sent to a physician to sign off on or modify. In Akido’s street medicine program in Los Angeles, ScopeAI enabled provider teams to double the number of patients they could serve, driving a 55% reduction in emergency department visits and achieving 82% retention at three months in a population with traditionally high dropout rates. The company has expanded into clinics in Rhode Island and New York, including a chronic-disease management program for New York City rideshare drivers. Akido now serves 500,000 patients annually across nearly 100 clinics and 26 specialties. 

AtaiBeckley
For bringing next-generation psychedelics into the mainstream
In July, Eli Lilly announced it would acquire AtaiBeckley in a deal worth up to $3.8 billion—a major validation of a pioneer in regulated psychedelic therapies. Its lead asset, BPL-003 (mebufotenin benzoate), is a nasal spray based on a compound found in the defensive secretions of the Sonoran Desert toad. After early studies showed substantial improvement over existing approaches to treatment-resistant depression, the FDA granted BPL-003 Breakthrough Therapy Designation in October 2025. The spray could shrink clinical visits to about two hours, versus six to eight hours for first-generation therapies based on psilocybin. With phase 3 trials initiated in June 2026, the drug could become the first next-generation psychedelic medicine to obtain FDA approval.

Axoft
For developing a more brain-friendly brain-computer interface
Made from a bio-inspired material called Fleuron that mimics the soft tissues of the brain, Axoft‘s minimally invasive brain-computer interface (BCI) can be surgically implanted through two tiny holes in the skull. With 32 times more sensors per thread than current flexible probes and 60% less signal loss than BCIs made from conventional polyimide, it gives high-resolution access to neural activity not available through traditional exams or external imaging. Because it can be safely implanted in any brain region, including previously unreachable deep areas, Axoft’s device is uniquely suited to evaluating patients in a coma or vegetative state. The device has been implanted in 11 patients so far across three clinical sites, including Mass General Brigham.

Neko Health
For making the annual physical fast—and kind of fun 
Cofounded by Spotify founder Daniel Ek and Hjalmar Nilsonne, Neko Health is reinventing preventive healthcare through a growing network of spa-like clinics offering a comprehensive health assessment in one hour. Combining data from its proprietary Dermascan imaging device, biometric measurements, blood testing, advanced sensor readings, and a consultation with a human physician, the Neko Health exam identifies early indicators of cardiovascular disease, metabolic conditions, circulation issues, and skin cancers. The company has opened two clinics in Sweden, six in London, and one in New York City. Neko Health has raised over $1 billion to fund growth, including a $700 million funding round this July.

Paytient
For making out-of-pocket health costs more manageable
Americans spent $98 billion out of pocket on medications in 2024, a cumulative 25% increase over five years, according to analytics firm IQVIA. Paytient’s healthcare affordability platform, which is typically underwritten by employers, acts like an interest-free line of credit to help people pay for things that health insurance doesn’t, including copays, coinsurance, and deductibles. Members get a Paytient card that pays providers in full up front, then repay over time via payroll deduction, bank account, or HSA/FSA. The company now serves more than 26 million members and partners with nearly 7,000 employers, insurers, and providers. In 2026, Paytient expanded into pharmacy benefits, partnering with GoodRx and Cost Plus Drugs and adding transparent drug pricing to its app.

SetPoint Medical
For easing rheumatoid arthritis pain without pills 
SetPoint Medical‘s is the first FDA-approved neuroimmune modulation device for rheumatoid arthritis. The multivitamin-size wireless neurostimulator is implanted on the vagus nerve and delivers a daily one-minute electrical signal to regulate inflammation without drugs. In a trial of 242 patients with RA, 75% of participants managed their symptoms with SetPoint alone at 12 months. Since the FDA nod in July 2025, adoption has accelerated—the therapy is now available in six markets, with expansion planned in up to 30 new cities by the end of 2026. In April 2026, the company began enrollment for a pilot study evaluating the device as a potential therapy for relapsing multiple sclerosis.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Adam Bluestein

The 7 next big things in foundational AI for 2026

6 days 5 hours ago

AI innovation may feel like it’s utterly dominated by a few giants, but the reality couldn’t be more different. These honorees have thrived by zeroing in on specific challenges, including teaching the technology to interpret sensor data, speeding up inference, and giving researchers better insight into how models actually work.

Archetype AI
For turning sensor data into intelligence
Large language models may know a lot, but because they have been trained on text and images, that limits their understanding of our world. By contrast, Archetype AI’s Newton foundation model can interpret data from cameras, lidar, radar, inertial measurement units, and other sensors used in enterprise domains such as construction, logistics, manufacturing, and urban planning. Customers ranging from the city of Bellevue, Washington, to data services firm NTT Data to construction giant Kajima Corporation have adopted the model, which outperforms the major general-purpose LLMs on sensor-related tasks.

Cerebras Systems
For putting inference’s pedal to the metal
If you’ve ever asked AI to do something and then drummed your fingers waiting for it to respond, you’ve run up against slow inference. To pick up the pace, Cerebras developed its own inference platform from the semiconductor wafer up. In January 2026, the company unveiled a partnership with OpenAI to launch a 750-megawatt deployment of its technology. Two months later, it announced that its systems had been deployed in Amazon’s AWS data centers. It’s also working with AWS on an AI architecture that pairs the companies’ technologies to quintuple a hardware footprint’s token capacity.

d-Matrix
For powering real-time AI
In June 2026, d-Matrix’s Corsair AI platform entered full production. It reduces typical latency inherent to AI by placing compute and memory alongside each other, an approach that an independent benchmark showed slashing AI response time to 2 seconds from 24 seconds. The company’s investors including Microsoft, SK Hynix, and Samsung, along with the Qatar Investment Authority and Singapore’s EDBI.

Goodfire
For taking the mystery out of models
Silico, Goodfire’s AI development and interpretability platform, is designed to overcome AI models’ notoriously opaque nature. It allows researchers to examine the innards of a model, make precision adjustments, and steer its behavior in ways that might otherwise be impossible. Mayo Clinic adopted Silico to catalog 4.2 million genetic variants and predict their likelihood of causing disease. Rakuten used it to excise sensitive data from its agent platform, resulting in 58% fewer hallucinations at approximately 90 times less cost than typical approaches.

Liquid AI
For helping AI think small
AI running at massive scale in data centers gets most of the industry’s attention. Liquid AI’s LFM2.5 is a set of AI models optimized to run on processors in laptops, smartphones, vehicles, and IoT devices—no internet connection necessary. Instead of being based on transformers like a conventional model, each one is customized by Liquid AI’s own meta-AI system to operate within specific processor and memory constraints. Chipmakers AMD, Intel, and Qualcomm are shipping LFM2.5 versions for their respective platforms. Last April, Liquid AI also signed a multiyear deal with Mercedes-Benz to embed the technology directly into vehicles.

Merge
For plugging enterprise AI into the real world
Released in October 2025, Merge’s Agent Handler lets organizations use AI to unlock the value of data that lives in their essential applications. Instead of engineering teams having to wire up Model Context Protocol (MCP) connections themselves, they can use Merge’s library, which covers of hundreds of enterprise tools, such as Salesforce, Workday, Gmail, and GitHub. These connectors are prebuilt and designed with security and observability in mind. Some 1,700 paying customers call on the platform for more than 1.1 billion daily API requests; it also powers Perplexity’s Enterprise Pro service.

Runpod
For delivering AI infrastructure as a service
Runpod is a cloud provider focused entirely on helping organizations train and deploy fast, reliable AI without having to invest in GPU hardware or manage it on their own. Its platform provides access to more than 30 Nvidia and AMD GPU models in 31 global regions and offers proprietary technologies such as FlashBoot, which speeds inference by cutting cold-start times to under 200 milliseconds. The company says it’s passed $120 million in annual recurring revenue from more than 1 million customers.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Harry McCracken

The 4 next big things in food and agriculture for 2026

6 days 5 hours ago

Climate change is making food harder to produce, even as agriculture remains a major source of emissions. At the same time, farmers are contending with labor shortages, rising costs, and pressure to get more out of every acre. New technologies are helping them do that, from robotic beekeeping and AI systems that reduce crop loss and pesticide use to tools that identify the genes behind more resilient crops.

Beewise
For automating beekeeping at scale
For commercial beekeepers, keeping tabs on thousands of hives across miles of farmland is a challenge. A hive can develop a health problem without anyone noticing, simply because it’s not physically possible to visit every hive often enough. ROBI, Beewise‘s solar-powered robotic beekeeper, is designed to help by autonomously moving down flexible rails that sit between rows of beehives. It captures images of each frame in a hive so software can analyze colony health. It can also feed bees and treat disease as needed. Some of the largest pollination providers in the U.S. are now beginning to roll it out.

Farmwave
For using AI to reduce crop loss
Farmers harvesting crops such as corn and soybeans can lose tens of thousands of dollars in produce because tractors struggle to adapt to varying field conditions, leaving portions of the crop unharvested. Farmwave uses cameras and AI to track grain loss in real time so farmers can adjust tractor settings, reducing loss by three to eight bushels per acre. The tech runs on Dell’s Pro Rugged tablets, designed to work in dusty, demanding field conditions. Thousands of images captured by the AI system each day are processed directly on the device, allowing the technology to work in areas with limited or no Wi-Fi connectivity.

Heritable Agriculture
For finding the genes behind better crops
Conventional plant breeding is slow—scientists can spend as long as ten years just figuring out which gene matters for a particular trait. Heritable Agriculture uses AI to identify key genes in 14 to 18 months. The startup spun out of X, Alphabet’s “Moonshot Factory,” in 2024 after five years of research. It uses deep learning and large language models to analyze plant data, including DNA and proteins, alongside environmental data on soil and water to help develop crops optimized for a particular location and adapted for climate change. In one project backed by the Gates Foundation, Heritable is developing drought- and heat-tolerant crops for sub-Saharan Africa.

Verdant Robotics
For slashing pesticide use with AI
Verdant Robotics’s SharpShooter technology, mounted on tractors, uses AI to aim herbicide directly at weeds and not at crops, reducing herbicide use by as much as 99%. The system builds a live digital twin of the field, including every crop plant and weed, and it targets unwanted plants with millimeter-level accuracy. Farms can save hundreds of thousands of dollars on labor and roll out treatment at the moments it’s most useful, something that’s challenging with current labor shortages. The payback period is between six and 18 months. In one study, yield at early harvest more than doubled.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Adele Peters

The 3 next big things in fintech, crypto, and blockchain for 2026

6 days 5 hours ago

Fintech and blockchain technology has seen its fair share of boom and bust cycles in the past decade, from the cryptocurrency explosion during the COVID pandemic to the AI era launched by ChatGPT. But the tech has continued to evolve in step with it all, and the work being done in this space is exciting—from companies that are challenging social norms to those that are betting on futuristic visions.

Mesh
For connecting crypto’s fragmented payment ecosystem
Even as cryptocurrency matures, a pain point for consumers remains: The system is fragmented by design. Hundreds of different blockchains, digital wallets, exchanges, and payment platforms exist as islands on their own. That may be frustrating for the more than 900 million global crypto users—who made over $27 trillion in transactions with stablecoins alone this year—as moving money around often requires custom engineering. Mesh bridges the islands. It built a layer of infrastructure that links wallets, exchanges, and platforms at a single point, turning a cacophony into a harmonious orchestration—a shopper in Lagos could pay in Bitcoin, Solana, or any other token owned, and a merchant in Manila could instantly settle in USDC, dollars, euros, yen, or any currency preferred. With Mesh, those conversions are automatic rather than manual. The company stands as a neutral party—it does not mint tokens, run a trading desk, or hold custody itself—and bills itself as future-proof for the age of AI agents, even giving a live demo of an AI-driven e-commerce transaction at Singapore’s TOKEN2049. In January, Mesh raised $75 million in funding at a $1 billion valuation. It powers crypto payments for PayPal and Kalshi, and partnered with Google for the emerging autonomous payments economy.

Seon
For making fraud intelligence portable across AI models
AI might enable more fraud, but Seon is enabling more fraud protection across AI bots. In June, the company released a fraud detection and anti-money-laundering tool that can be freely layered onto any existing AI model—from Anthropic’s Claude to OpenAI’s ChatGPT to Google’s Gemini. That’s in stark contrast to other fraud tools on the market, which lock customers into proprietary experiences that don’t talk to each other. According to Seon, companies often stack those disconnected tools—one for identity checks, one for activity monitoring, et cetera. But Seon’s “portable intelligence layer,” or “Model Context Protocol,” sends its 900 real-time signals to any AI, allowing it to seamlessly reference them across the full user journey. And that makes fraud detection more effective—for example, it could catch criminal rings by flagging clusters of activity that only seem suspicious when put together versus being viewed in isolation. Seon processes 15 million transactions daily and is used by more than 5,000 businesses globally across fintech, retail, and gaming, including Afterpay, Bally’s, and Tecovas. It helped a top fast-casual restaurant chain across North America, Europe, and the Middle East cut fraud by 40%. In 2025, it grew its annual recurring revenue by 80%, from new customers and deeper adoption.

Wealth.com
For bringing estate planning into the digital age
Nearly 3 in 4 Americans regard estate planning as important—yet simultaneously, nearly 3 in 4 Americans lack even a basic estate plan, according to Caring.com. That’s begotten unfortunate consequences: More than half (58%) of families have squabbled over inheritances after a death in the absence of a proper estate plan—which has, counterproductively, locked up that wealth for months if not years, InvestmentNews reports. Why don’t Americans plan for post-mortem? Studies suggest it’s a combination of confusion about the process, concerns that it will be too costly, and the belief that they don’t have enough net worth to justify an estate plan. But with new AI technology that cuts expensive attorneys and lengthy paperwork out of the equation, Wealth.com is hoping to de-frictionize the process. Its engineering teams leveraged artificial intelligence to translate thousands of pages of state-specific legislation and factor in decades of estate-planning logic, creating a platform that can walk clients in all 50 states (plus Washington, D.C.) through the whole journey, end to end. It claims that what once took months can now be done in 30 minutes. Since its founding in 2021, Wealth.com has delivered 100,000-plus estate plans and is used by 5 out of 7 of the nation’s largest private banks, representing more than $15 trillion in client assets. Following four consecutive years of over 300% revenue growth, in 2026, the company raised $65 million from Google Ventures, Charles Schwab, Citi Ventures, and other investors.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Connie Lin

These innovations of 2026 could have a particularly broad impact

6 days 5 hours ago

Some innovations have potential beyond the bounds of a single industry. These honorees include a company that is combining AI and advanced genetic life science to better track disease pathology, and another developing models that could help avoid animal testing by simulating human organ functions. 

Algen Biotechnologies
For blending genetics and AI to advance pathology
One of the most promising health applications for AI is earlier identification of genes that can be targeted by therapies to reverse disease processes. Spun out of Nobel Laureate Jennifer Doudna’s lab, Algen is the creator of AlgenBrain. It uses CRISPR and AI to better understand disease biology and accelerate next-generation approaches. The system maps causal links between gene regulation and disease progression, going beyond data analysis to generate solutions. The company recently announced a $555 million partnership with AstraZeneca to develop AI-powered drug discovery, giving Algen access to the pharmaceutical giant’s immunology pipeline.

Emulate
For developing human organ simulators that can supplant animal testing
Organ-on-a-Chip technology from Emulate uses microfluidic devices containing human cells to replicate key aspects of human organ functions. That offers more relevant data for modeling—for example, drug reactions—than traditional 2D cell culture models. Emulate’s next-generation platform focuses on scalability, attacking the high-cost and labor-intensive workflows that its first systems required. The company’s Human Liver Chip is in the final stages of the FDA’s ISTAND qualification program, which could enable it to partially replace animal testing in regulatory submissions for pharmaceuticals.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Ross Rubin

These established companies are still innovating like startups

6 days 5 hours ago

As companies emerge from early startup stage, pressure mounts to focus on execution. But they must also have an eye toward opportunities to improve, expand, and serve evolving marketplace needs. This year’s honorees have used AI to streamline and automate common back-office tasks, help companies meet mission-critical requirements, and serve doctors and mothers by more precisely determining pregnancy due dates.

Rippling
For teaching AI “that’s how we do things here“
The more AI understands about our work, the better it can help us navigate and perform tasks in that world. Rippling is a platform focused on streamlining and automating many of the administrative tasks in areas such as HR, IT, and finance. Its agentic prowess stems from having access to the native data structures, context, and controls defined within a company. That creates outputs that reflect the actual state of a business, helping humans in these roles focus on more strategic tasks. The company, which largely serves mid-market customers, recently crossed $1 billion in annual recurring revenue and raised $450 million at a $16.8 billion valuation. 

Seekr
For bringing AI to mission-critical tasks
While many organizations are piloting AI across a range of jobs, the vagaries around its operation have kept it out of many mission-critical applications. Seekr’s SeekrFlow aims to change that with an end-to-end AI platform for creating, deploying, and managing LLMs using an organization’s own data. Designed for enterprises, government agencies, defense organizations, and regulated industries, it addresses challenges around such issues as data quality and oversight via high-quality AI datasets and domain-specific models and agents. Earlier this year, the company partnered with General Dynamics Information Technology to build agentic AI solutions for federal agencies. It’s available now on AWS GovCloud.

Ultrasound AI
For delivering more accurate pregnancy due dates
For hospital staff, an expectant mother’s due date is key to a range of obstetric care decisions, such as how to time an induction or cesarean or when to prepare for a potential high-risk birth. Predictions made via traditional means can be off by more than two weeks. Ultrasound AI‘s Delivery Date AI (DDAI) replaces the manual formula measurements with one derived from analysis of a standard ultrasound image in less than a minute, creating a more accurate delivery date prediction. In February, Ultrasound AI received FDA De Novo clearance for DDAI tech, paving the way for broader adoption.

The companies and individuals behind these technologies are among the honorees in Fast Company’s Next Big Things in Tech awards for 2026. Read more about the winners across all categories and the methodology behind the selection process.

Ross Rubin
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