Source: Fast Company, Shivani Siroya
Photo: Getty Images

How artificial intelligence and blockchain technology are changing the future of finance

In a year defined by breakthroughs in artificial intelligence and blockchain technology, you might think that all this incredible innovation has made its way into the hands of the people who need it most. But you’d be wrong.

Much of the world’s population lacks access to the financial services they need, despite having trillions of dollars in economic power. Being excluded from the legacy financial services industry means having to navigate their daily lives without access to savings, credit, bill payment tools or the ability to affordably transfer money.

Some refer to this group as “the missing middle,” but at Tala, we call them the global majority. We’ve spent the last 10 years serving over 10 million people from this often-overlooked global population and have seen their struggles firsthand.

And while this new wave of technology hasn’t yet hit the mainstream, I’m more optimistic than ever that 2025 will change that. Here are three ways I predict the new year will change, thanks to fintech.

1. Credit reimagined

Most Americans don’t think twice about using their credit card to buy groceries. But what if you didn’t—or couldn’t—have access to one? That’s an unfortunate reality for billions of people around the world because traditional institutions still rely on a system created nearly a half-century ago to determine creditworthiness.

While we’ve seen some progress in emerging markets—from buy-now-pay-later services to pay-as-you-go features in superapps—we still have a long road ahead. The entire system needs to be reimagined, and it needs to happen soon.

Something as simple as offering unsecured credit products, for example, can simultaneously increase credit access and help develop new underwriting models designed for the 21st century.

And I believe that next year we will see this evolution begin as companies leverage modern, real-time, and forward-looking data to determine someone’s creditworthiness.

2. The LLM leapfrog effect

It’s no secret that artificial intelligence has taken fintech—and the world—by storm. But I think many are missing the big picture, especially when it comes to the power of large language models (LLMs).

LLMs have access to an incredible breadth of public knowledge but lack important context and non-public data to solve specific problems. The global majority is one example of a segment that isn’t well represented in public data. The real opportunity exists in combining the power of existing LLMs with a company’s expertise, custom tools, and private data to supercharge their products and services.

And as we look ahead to next year, I believe we’ll see more companies integrating LLMs into their tech stacks to improve their existing workflows and discover new and innovative ways to serve their customers.

3.The year of the stablecoin

Unlike crypto tokens, stablecoins are pegged 1:1 to a specific currency like the U.S. dollar while still operating on blockchain rails. One U.S. dollar stablecoin, for example, aims to always be worth exactly one U.S. dollar. And while that might not sound like a revolutionary concept on the surface, the implications are massive.

This technology enables near-instant transactions to occur 24/7, 365 days a year without geographic restrictions, and at a fraction of the cost of traditional financial institutions. This eliminates the need for intermediaries like banks that charge high fees, take days to process a single transaction, and are only open during specific time windows during the week––a price the global majority can’t afford in time or money.

We’ve already seen strong momentum in the global adoption of stablecoins and I believe next year will mark a huge step forward in mainstream use of this technology, particularly in historically underserved markets.

2025 and beyond

The road ahead won’t be easy, but this work is incredibly important. There are trillions of dollars’ worth of economic power just sitting on the sidelines and I believe 2025 will be the year we unleash it.

Shivani Siroya is founder and CEO of Tala.

https://www.fastcompany.com/91260788/3-fintech-predictions-that-will-shape-2025

Source: Dezeen, Saudatu Bah
Photo: Courtesy of LeafyPod

Technology brand LeafyPod has unveiled an AI-powered smart planter at this year’s Consumer Electronics Show (CES).

Made from durable plastic materials, the LeafyPod aims to address what the brand identifies as the four main causes of plant death: soil moisture, light, temperature, and humidity.

“The materials were chosen specifically for their resistance to water exposure and ability to maintain structural integrity over time”, Cleo Song, co-founder of LeafyPod, told Dezeen.

The device has sensors that detect light, humidity, and temperature and relay the data to the LeafyPod app.

“Our AI-powered watering system automatically adapts to each plant’s specific needs by monitoring environmental conditions and adjusting the watering schedule accordingly, ensuring optimal care regardless of the plant variety”, Song said.

The LeafyPod app works alongside the plant, learning its routine over time and automatically adjusting the watering schedule for optimised care.

“The planter’s clean, minimalistic design in classic white conceals its sophisticated technology – including multiple environmental sensors and watering systems”, Song continued.

Users can recharge the device, while a built-in water reservoir ensures the plants stay hydrated, even during extended trips.

“The app sends timely notifications for all maintenance needs, from water refills to filter cleaning or replacement”, Song said.

“The cordless design with USB charging capability further simplifies the user experience”.

The gadget can be voice-controlled by integrating it with smart devices like Alexa and Google Assistant.

The device features a dual-filter system, with a reusable filter on the pump that can be cleaned and a replaceable filter at the bottom of the transparent inner pot.

The LeafyPod also has an adaptive watering system that adjusts based on plant type and real-time environmental data.

“We designed the water tank to require refilling only once every two weeks to a month, optimizing water usage while maintaining plant health”, Song said.

“The system’s AI-driven approach helps prevent both overwatering and under-watering by continuously monitoring soil conditions and adjusting water delivery accordingly.”

Other devices showcased at this year’s CES fair include the Hormometer hormone testing kit and a solar-powered car.

https://www.dezeen.com/2025/01/17/leafypod-unveils-ai-powered-self-watering-smart-planter-at-ces

Source: ModernRetail, Mitchell Parton
Photo: Courtesy of Wing

After flying drones from Walmart stores and fast-food restaurants to shoppers’ backyards, Alphabet-owned Wing is now taking flight from shopping malls in Texas.

Wing said in December it would partner with Brookfield Properties and DoorDash to offer drone delivery from more than 50 merchants at two malls in the Dallas-Fort Worth metro area: Stonebriar Centre in Frisco and Hulen Mall in Fort Worth. The service is available to restaurants and retailers that deliver through DoorDash and are also tenants at either of the malls.

Residents within 4 to 6 miles of the malls can use the DoorDash app to order full meals, hot coffees, cold beverages and retail items under 3 pounds. This is a continuation of DoorDash and Wing’s partnership, which first began last March to expand the reach of drone delivery to more customers and provide an additional mode of transport for DoorDash orders.

Jesse Suskin, head of corporate affairs at Wing, said the company identified malls as a good fit for the program because they are close to many people’s homes and have plenty of flat spaces, such as parking lots and garages. It opens up dozens of new restaurants and retailers within the mall to drone delivery.

“It’s kind of a nice marriage of three companies that have a forward, leading approach to last-mile delivery,” Suskin said in an interview. “When moving food, we’re going to be some of the fastest in the game in terms of being able to move from when somebody places an order on their DoorDash app at their home to when they get that package delivered.” Wing’s DoorDash deliveries take less than five minutes on average, the company said.

This also comes as mall owners have been looking for new ways to modernize their properties to make up for lost anchor tenants and changing demand from younger shoppers, such as building apartments, adding more restaurants and entertainment venues and building housing on site.

Katie Kurtz, Brookfield’s svp of business development, told Modern Retail in an interview that it was important to the company to be the first mall operator to offer drone delivery. “We’re always looking for what’s innovative — how do we think outside the box, how do we as Brookfield offer our tenants something that is above and beyond the norm.” She said Brookfield is in talks with Wing to expand the program to at least two or three more regions, depending on FAA clearances.

“We still want [shoppers] to be able to purchase from in-mall tenants and be able to serve them in the way that they need,” Kurtz said. “While traffic is up and shoppers are back — and I think that we’ve seen this post-Covid trend of people wanting to be out and shop in person — there’s also just, logically, so many hours in the day sometimes where you can’t physically get to the mall and or to a store.”

Wing continues to scale up its operations in Texas. It’s a region where multiple drone delivery companies — including DroneUp, Wing and Zipline — are testing new technology to deliver packages. In October, Wing’s head of operations Nate Milner said the company had launched a new facility there every two weeks. About a year ago, Wing announced an expanded partnership with Walmart in the area, in which it would expand its drone delivery offering to 1.8 million more households in the region.

“For a subset of our customers, they love not only that it’s fast, that it’s a drone delivering it for the environmental benefit or for the excitement of their kids, maybe being in the front yard or backyard to watch that drone deliver the package,” Suskin said.

So far, drone delivery is limited by package size and delivery range. Brad Jashinsky, director analyst for Gartner, said that as drone delivery services expand their reach and capabilities, they could eventually play a bigger role in helping retailers use stores to fulfill online orders instead of solely relying on distribution centers.

“This could help bring down fulfillment costs as regions allowing drones expand, delivery ranges increase, payloads expand and costs come down,” Jashinsky said in an email. He added that being listed on DoorDash, whether for drone-delivered items or not, provides a large increase in exposure for retailers.

https://www.modernretail.co/technology/why-wing-chose-malls-as-the-next-frontier-for-drone-delivery

Source: Fast Company, Elizabeth Segran
Photo: Ahmet Kusakog/iStock/Getty Images Plus

Estée Lauder Companies, which owns Le Labo and Jo Malone London, is partnering with a startup called Exuud that prevents your nose from getting desensitized.

We’re in a golden age of home fragrance. Everywhere you go, from Sephora to Whole Foods, you’ll find candles, diffusers, and plug-ins, all designed to fill rooms with irresistible scents.

There’s only one problem: Humans have evolved to stop perceiving scents after a short period to prevent overstimulation, a condition known as olfactory blindness. “It happens in seconds,” says Pam Dalton, an olfactory scholar at Monell Chemical Senses Center. “Our brain is optimized to detect changes in scent rather than continuous scents to help us respond to dangers like, for instance, gas leaks.”

Estée Lauder Companies—the $15.6 billion beauty conglomerate that owns fragrance brands like Jo Malone London, Le Labo, and Kilian—has just invested in a new technology called Exuud that promises to change the way we experience scents at home. Exuud has developed a new way to control the concentration of aromatic molecules in a given environment, and by modulating its intensity, it believes it can prevent our noses from getting desensitized. Estée Lauder Companies believes this technology could be a game-changer, giving it a leg up in the $24 billion global home fragrance market.

The Pandemic Fragrance Boom

When Estée Lauder founded her eponymous brand nearly eight decades ago, she believed that luxury fragrance could become a big business. Back then, women tended to rely on men to buy them perfumes, much like with jewelry. Starting in the 1950s, Lauder had the idea of created a scented bath oil that women would feel comfortable buying themselves. Shortly thereafter, she started marketing perfumes to women. With this heritage, it makes sense that Estée Lauder Companies has chosen to acquire many fragrance brands.

During the pandemic, a curious thing happened: While people were stuck at home during lockdown, they developed a voracious appetite for new scents. It was an unexpected turn for a moment of relative solitude. For decades, the fragrance industry had marketed scents as something you wore for other people. But suddenly, even though they were’t going out, people were spraying themselves with scents throughout the day. This led to a corresponding growth in the home fragrance category. “It became clear people enjoyed the smell of these perfumes, and wanted to refresh it,” says Sumit Bhasin, SVP of corporate fragrance research and development, at Estée Lauder Companies. “They wanted their homes to be full of fragrances.”

Today, the luxury fragrance sector is continuing to grow, with sales increasing by 8% in the first half of 2024 to $15.3 billion. Many perfume brands began expanding their home fragrance offerings. And Sephora, the largest high-end beauty retailer in the world, has been expanding its indie fragrance offerings, which includes both body and home products. Estée Lauder Companies also wants to tap into this booming industry with better technology.

The Fragrance Delivery Problem

Delivering scent into a room is more difficult than you’d think, particularly when it comes to fine fragrances, which are carefully designed to balance top, middle, and bottom notes. Heat-based systems, like candles and diffusers, break down top notes, diminishing the overall scent. Meanwhile, aerosol-based systems, like sprays and some plug-ins, tend to overwhelm your senses by sending millions of fragrance molecules into the atmosphere. This hastens olfactory blindness.

During the pandemic, Abhishek Breja–along with his wife Neerja–had the vision of coming up with a new technology that would allow you to control and program how much fragrance was released into a space. He brought on Jesse Killion, an engineer who specializes in technologies that involve heat transfer. Together, they came up with a technology that converts liquid perfumes into solid form encapsulated in beads, then releases it into a gas state with a new level of precision. They’ve currently filed 10 patents for this new system, and the technology through which they convert this liquid into a solid is a trade secret.

At first glance, the Exuud’s “smart fragrance delivery system” looks like a vase. The key to this technology are the capsule of beads inside. When air wafts over the beads, it releases aromatic molecules into the air, creating the scent. “This is how flowers release their fragrance,” says Breja. “This technology is inspired by nature.”

After weeks or months of using the device, all the fragrance molecules will be released into the air. You then dispose of the bead capsule, and buy a new one. The Exuud team has spent time trying to make the system as eco-friendly as possible. The beads are made from a polymer derived from plants that will biodegrade at the end of its life; it has an 80% smaller carbon footprint than comparable petroleum-derived plastic beads.

But the important thing about this innovation is that Exuud can precisely control how much fragrance is released by controlling the airflow. It’s possible to program the device to change the airflow, which changes the intensity of the fragrance in the air. “With spray devices, like a Glade plug-in, you’re flooding the room with a burst of fragrance molecules,” says Killion. “But here, we can release airflow in a controlled way.”

Breja believes that this is the way to overcome olfactory fatigue. By releasing fragrance at intervals, increasing then decreasing the volume of aromatic molecules in the air, our noses will not adapt to the scent. It’s important to note that this hasn’t been tested or verified by scientists; so far, he is basing this on anecdotal evidence.

Dalton, the olfactory scholar, has not seen this system. However, her research suggests that while changing the intensity of a fragrance may allow you to keep perceiving it over the short term, it is likely that our brains will filter out the scent over the long term. This is why people who deal with chemicals in factories or waste management are able to filter out these smells, even though their intensity changes over time. “The solution would be to change the fragrance every so often, so you can continue perceiving the scent,” Dalton says.

From a luxury fragrance perspective, this technology appears to be much better at preserving the complexity of the scent. Since there is no heat involved, even the most volatile top notes remain intact.

An Exclusive Partnership

Estée Lauder Companies has invested an undisclosed amount in Exuud, and it has also signed an exclusive commercial agreement that allows the conglomerate to integrate its devices into its fragrance portfolio. It expects the first products to launch in 2025.

Different brands will customize Exuud’s device in a way that fits into their brand image. Le Labo could create a device that reflects its industrial-chic aesthetic; Jo Malone may create something that is more classic and feminine. But the bead technology inside will be the same. Each brand will effectively white label Exuud’s technology, creating capsules of beads that look like just another product within its line.

Exuud is developing an app that will automate the way the device operates. Users can set the device to release scents at particular times of the day, for instance, or change the intensity of the scent to their liking. Exuud can even identify when the capsule of beads may be running out of fragrance, and prompt the user to order more.

While the pandemic deepened the world’s love of home fragrance, Estée Lauder Companies believes that it can build on the current explosion in the fragrance market thanks to this new innovation. And brands within the portfolio are currently at work incorporating the technology into their product lines. “We invested in this technology because we think it’s more than just an incremental improvement,” says Bhasin. “We think it could change the way we experience fragrance.”

ABOUT THE AUTHOR

Elizabeth Segran has been a staff writer at Fast Company since 2014. She covers fashion, retail, and sustainability. She has interviewed Virgil Abloh, Mara Hoffman, Telfar, Diane von Furstenberg, and Ulla Johnson, among many other designers.

https://www.fastcompany.com/91256985/say-goodbye-to-your-candles-estee-lauder-just-designed-a-better-way-to-make-your-home-smell-good

Source: ExtremeTech, Adrianna Nine
Photo: Artist’s rendering of a Mars lander that could retrieve Perseverance’s samples and send them to Earth. (NASA/ESA/JPL-Caltech/GSFC/MSFC)

The agency is starting down two different paths toward the samples’ return, but only one will bring the red rocks home.

NASA kicked off the new year with a major announcement: It’s officially tackling the issue of bringing Mars samples to Earth. Though the agency’s Perseverance rover started collecting Martian regolith four years ago, the Mars Sample Return program’s rising costs have made it difficult for officials to land on a specific transportation plan. Now, after investigating a handful of alternate return strategies, the agency has selected two to pursue this year. But only the winning strategy will bring the red rocks home.

In a media briefing on Tuesday, NASA Administrator Bill Nelson and Science Mission Directorate leader Nicky Fox explained that NASA’s original sample return plan had been nixed the year prior. The initial plan would have involved a Mars lander to which Perseverance could have passed the baton, allowing a rocket within the lander to depart from Mars and hop on over to the Moon, where the samples would be retrieved. But according to Nelson, that strategy would have brought the Mars Sample Return program’s total cost to $11 billion, and the samples wouldn’t have made it to Earth until 2040.

“That was just simply unacceptable,” Nelson said during the briefing.

Instead, NASA pieced together a Mars Sample Return Strategic Review team, which would field studies focused on various return methods from across the aerospace industry. The team investigated or rejected strategies based on their ability to reduce risk, cost, and the mission’s timeline. In the end, it chose two methods to begin pursuing in 2025.

The first method involves NASA’s existing “sky crane” architecture, which it successfully used to land Curiosity in 2012 and Perseverance in 2021. This approach uses a large heat shield and parachute for the spacecraft’s initial descent, then slows it down with retrorockets before gently placing the spacecraft on the planet’s surface with a strong cable. Theoretically, the sky crane approach could allow NASA to land a spacecraft on Mars, snag Perseverance’s samples, and return directly to Earth—a far simpler, and therefore cheaper, alternative to NASA’s original plan.

NASA’s second plan is to leverage existing commercial partners, such as SpaceX or Blue Origin, who could devise their own retrieval methodologies. This approach would bring the samples to Earth as early as 2035 and land the Mars Sample Return program’s total cost between $5.8 and $7.1 billion. Nelson said NASA is currently exploring a number of these avenues, but did not specify what the actual return might look like.

For both of these paths, success means bringing home 30 of Perseverance’s 43 cigar-sized titanium sample tubes. And while NASA is now investigating the viability of both plans, only one will have the honor of retrieving the samples. The agency expects to make a final decision in the second half of 2026; the timing of the samples’ return will then depend on how efficiently Congress can fund the mission.

“The samples that we have been collecting on Mars are very carefully selected to provide groundbreaking opportunities for research,” Fox said during the briefing. “Bringing them back will revolutionize our understanding of the planet Mars and indeed our place in the solar system.”

https://www.extremetech.com/science/nasa-is-one-step-closer-to-bringing-mars-samples-to-earth

Source: ModernRetail, Anna Hensel
Photo: Courtesy of Babylist

After devastating wildfires ripped through the Los Angeles area, brands and retailers have been scrambling over the past week to find ways to help residents impacted by the destruction.

Altogether, more than 40,000 acres have burned, with fires in the Palisades and Eaton neighborhoods causing some of the worst damage. Roughly 88,000 people were still under evacuation orders on Wednesday, and thousands of commercial and residential structures have been destroyed in the fire. The people who lost their homes now face the daunting task of figuring out how to replace everything, from clothes to personal care products to electronics.

That’s where brands are stepping in to help. Julia Beilman, vice president at investment firm TCG, has spearheaded a spreadsheet of brands that are providing free items, product replacement and other support to families impacted by the wildfires. The spreadsheet now includes more than 230 brands, ranging from Alo Yoga to Our Place to Figs.

Now, the focus has shifted to how brands can work together and share resources. Brands are working with various community organizations to figure out what items first responders or families who lost their homes are most in need of.

Lauren Kleinman, founder and CEO of performance PR agency Dreamday, who has worked with Beilman to update and circulate the spreadsheet of brands providing products, said in an email that “we’ve learned that some affected families, having lost everything and temporarily relocated, need time before they can accept these products. That’s why we’ve designed this as an enduring resource they can access when ready.” Kleinman added that she and Beilman were updating the spreadsheet hourly with new brands.

Others have turned their stores or headquarters into ongoing hubs for donations. Kidswear brand Même is accepting donations through the mail or in person at its Los Angeles headquarters through Friday, January 17. On its Instagram, Même outlined which products it needs, ranging from P100 and KN95 masks to diapers and baby wipes to new children’s blankets.

Babylist, which creates registries for new parents, is welcoming families impacted by the wildfires to its Beverly Hills showroom on January 21 and 28 to receive donations. Babylist organized the donation drive in partnership with Meena Harris and accessories brand Stoney Clover Lane. The company is asking people to RSVP ahead of time so it can better gauge the number of families who want to attend. Brands can fill out a form if they are interested in donating products.

Molly Goodson, vice president of brand and media at Babylist, said many brands have donated personal care and beauty products. Right now, Babylist is still looking for more donations of gear like bassinets and strollers.

What’s top of mind for Goodson and other brand executives she’s spoken with is figuring out how to show up in a way that’s most helpful to customers of a particular brand. For example, in partnership with formula brand Bobbie, Babylist hustled to make free cans of Bobbie available at the Babylist showroom starting on January 13 because “waiting ten days to be able to grab that formula is not feasible.”

“We are stronger together when we figure these things out together,” Goodson said. “Every brand that I talk to wants to do something, wants to show up…it’s unlike anything I’ve ever seen.”

Bobbie has participated in donation drives hosted by Même and Babylist and has its own scholarship program, Give a Can, where people can gift a can to parents in need.

Michele Lampach, the lead of Bobbie’s social impact policy arm, Bobbie for Change, said in an email that 1,600 cans were gifted in the first five hours after Bobbie posted about its relief efforts on Instagram. For any parents who have been impacted or lost their homes in the fires, Bobbie is also offering to cover the rest of their feeding journey up until their baby turns one.

Goodson said that Babylist has also been sending emails to its Los Angeles customer base, asking them what would be most helpful right now. She said the feedback she’s gotten from people is that “social media is really loud right now, and for families going through this, it can feel extremely overwhelming.”

Goodson added that Babylist is “focused on the long game” — and is working with local organizations to ensure that products are distributed equitably.

Ghia founder and CEO Mélanie Masarin, who circulated a list of ways that people can help on the brand’s Instagram account, said in an email that “we’re still working to channel specific items like lip balms, energy drinks, hand creams, and sunscreen to first responders and donation centers.” Requests for men’s clothing, shoes, socks and underwear are also high.

She said that she’s “truly overwhelmed by how brands and their executives have mobilized to help LA businesses and wildfire victims.” She added that what she’d like to see in the weeks to come is “brands and individuals outside of California continuing to support LA and not canceling their events here.”

“It’s crucial to keep bringing jobs to the city, especially as many people who paused their lives to help their communities are now deeply concerned about what the next few months will hold,” Masarin wrote.

https://www.modernretail.co/operations/brands-like-babylist-and-bobbie-are-sharing-resources-to-help-victims-of-the-la-wildfires

Source: Knowledge@Wharton, Seb Murray
Photo: Illustration of a person in a suit with text bubbles and graphic elements floating above their shoulders.

New research from Wharton’s Philip Tetlock finds that combining predictions from large language models can achieve accuracy on par with human forecasters.

Decision-makers have long relied on the “wisdom of the crowd” — the idea that combining many people’s judgments often leads to better predictions than any individual’s guess. But what if the crowd isn’t human?

New research from Wharton management professor Philip Tetlock finds that combining predictions from multiple artificial intelligence (AI) systems, known as large language models (LLMs), can achieve accuracy on par with human forecasters. This breakthrough offers a cheaper, faster alternative for tasks like predicting political outcomes or economic trends.

“What we’re seeing here is a paradigm shift: AI predictions aren’t just matching human expertise — they’re changing how we think about forecasting entirely,” said Tetlock.

Dubbed as the “wisdom of the silicon crowd” by the Wharton academic and his co-authors — Philipp Schoenegger of London School of Economics, independent researcher Indre Tuminauskaite, and Peter Park from Massachusetts Institute of Technology — this approach highlights how groups of AI systems can provide reliable predictions about the future.

By pooling predictions from multiple LLMs, the researchers present a practical method for organizations to access high-quality forecasting without relying solely on expensive teams of human prognosticators.

“This isn’t about replacing humans, however,” Tetlock said, “it’s about making predictions smarter, faster, and more accessible.”

How Do AI Predictions Work?

Individually, AI models like GPT-4, made by Microsoft-backed OpenAI, have struggled with forecasting. Previous studies revealed that their predictions were often no better than random guesses. However, Tetlock’s paper, “Wisdom of the Silicon Crowd: LLM Ensemble Prediction Capabilities Rival Human Crowd Accuracy,” found that combining predictions from multiple models significantly boosted their accuracy.

So how does it work? The magic lies in how errors balance out. Just as human crowds average out individual biases, combining AI models cancels out inconsistencies in their predictions. Each model brings a slightly different perspective, much like human forecasters with varied expertise and experiences. “Just how human crowds balance individual biases, AI ensembles turn competing perspectives into consensus,” Tetlock said.

His study also found that AI predictions were greatly improved — between 17% and 28% — when informed by human input, such as insights from forecasting tournaments, where people compete to predict future events accurately. These competitions provide valuable, real-time data that AI systems can incorporate into their predictions.

“The best forecasts come when human intuition meets machine precision,” said Tetlock.

Interestingly, though, the researchers found the best results came from simply averaging human and AI predictions, rather than relying on the AI to synthesize them. This highlights a key takeaway: while AI is advancing, human input still plays an important role in creating the most accurate forecasts.

Tetlock and his co-authors put their methods to the test in real-world scenarios by carefully designing questions and situations that the AI models hadn’t encountered during their training. This ensured that the AI wasn’t just “cheating” by regurgitating memorized information.

Benefits and Limitations of AI Forecasting

The results were promising but revealed some challenges. For example, the AI models struggle when there’s a significant time gap between their training data and the events they’re predicting. This lack of up-to-date knowledge can reduce accuracy.

Additionally, the AI systems often exhibit overconfidence, assigning higher probabilities to outcomes that don’t align with the available evidence.

“Resolution” is a technique that could be used to fix this issue by sharpening predictions to clearly distinguish between what’s likely and unlikely. The goal is to assign higher probabilities to events that actually occur and lower probabilities to those that don’t, ensuring forecasts are both confident and accurate.

“The key to resolution is confidence with clarity — bet big on what’s likely and back off where it’s not,” Tetlock explained.

With tools in place to overcome these hurdles, the study demonstrates the practical value of AI in forecasting. In areas such as politics and economics, where big decisions depend on precise predictions, combining forecasts from LLMs is a practical, scalable, and efficient approach.

“This is just the start. As we refine these systems, they’ll not only get more accurate but also change how we make high-stakes decisions,” Tetlock said. “The human forecasters in our comparison baseline were educated, reasonably numerate adults — but not the elite of forecasters on the public platforms (e.g., superforecasters). That is a challenge the LLMs have yet to beat.”

For many organizations, the future of forecasting may be written not just by human crowds but by silicon ones as well.

https://knowledge.wharton.upenn.edu/article/can-ai-predict-the-future

Source: ExtremeTech, Adrianna Nine
Photo: Wladimir Bulgar/Science Photo Library via Getty Images

The model is the first of its kind to use multiple types of imaging and language-based data to assess a cancer patient’s health.

Stanford Medicine has developed an artificial intelligence model that can accurately predict cancer patients’ prognoses and responses to treatment. The first of its kind to leverage multiple types of imaging and language-based data, the model has already shown promise with several forms of cancer, including lung cancer, gastroesophageal cancer, and melanoma.

Over the last few years, researchers have created a range of experimental AI models that examine imaging data for tiny signs of cancer that doctors and radiologists might easily miss. Early tests show that these models are highly effective. Sybil, a model developed by MIT and the Massachusetts General Cancer Center, can predict patients’ one-year lung cancer development with an 86% to 94% accuracy rate, while Harvard Medical School’s pancreatic cancer prediction model can map a patient’s three-year prognosis with 88% accuracy. Another MIT model even spots signs of the riskiest forms of breast cancer to shield patients from overtreatment.

Impressive as these models are, they share in common one essential shortcoming: They’re only capable of analyzing one form of data at a given time. Each model looks at MRI scans or CT scans or X-ray images or microscopy slides, then identifies areas of concern within that dataset. Even Microsoft’s multi-diagnostic AI model, which accepts a whopping nine forms of imaging data, must examine those types of imaging separately.

Stanford Medicine’s model, MUSK (short for multimodal transformer with unified mask modeling), looks at several types of data at once. In a paper for Nature, the researchers write that MUSK was trained on 50 million pathology images and 1 billion “text tokens” from more than 11,500 patients. Although the images depict different forms of cancer across X-rays, microscopy, and CT and MRI scans, the text tokens represent language-based medical data—exam notes, communications between specialists, and so on—associated with various cancer diagnoses.

MUSK’s ability to analyze multiple types of data simultaneously mimics how doctors assess a person’s imaging results and health records. It also allows MUSK to assist doctors in predicting prognoses, not making diagnoses, the latter of which most medical AI models are focused on.

Across the 16 major types of cancer on which MUSK was trained, the model is capable of accurately predicting a patient’s disease-specific survival 75% of the time, according to a Stanford Medicine release. That’s an 11% improvement over doctors’ average accuracy rate, which hovers around 64%. MUSK has also correctly identified which non-small cell lung cancer patients would benefit from immunotherapy 77% of the time (beating doctors’ 61% accuracy rate) and predicted which melanoma patients were most likely to relapse within 5 years of initial treatment with 83% accuracy.

“The biggest unmet clinical need is for models that physicians can use to guide patient treatment,” said senior study author and radiation oncologist Ruijiang Li. “Does this patient need this drug? Or should we instead focus on another type of therapy? If we can use artificial intelligence to assess hundreds or thousands of bits of many types of data, including tissue imaging, as well as patient demographics, medical history, past treatments, and laboratory tests gathered from clinical notes, we can much more accurately determine who might benefit.”

https://www.extremetech.com/science/stanford-medicines-ai-model-accurately-predicts-cancer-prognoses-treatment

Source: ModernRetail, Mitchell Parton
Photo: ModernRetail

ThredUp’s chief product and technology officer, Dan DeMeyere, admits that shoppers can be overwhelmed when searching on the resale platform, which has more than 4 million unique items. Because of that, the company first looked to search when beginning to implement generative AI features to improve the shopping experience.

“If you came and you searched for, like, ugly Christmas sweater one year ago, you’d get no results because nowhere would you find ‘ugly’ or ‘Christmas sweater’ in our database,” DeMeyere said. Now, searching for that, or even Star Wars memes or “mermaid core,” will get you relevant results. Customers have realized that and changed how they use the search bar, he said. “We saw the diversity of search terms triple within less than a year.”

The natural-language search tool is one of three customer-facing AI shopping features ThredUp launched in 2024. The others were image search and a chatbot that creates tailored outfits from a given prompt. The company also found people using any of these three features are 55% more likely to return within the next seven days, and they’re 65% more likely to get to an item that they like — as in, they add it to their cart or press the favorite button.

Many of the largest retailers made major investments in generative AI this year and have reported financial payoffs in doing so. They have used it for personalized search tools, virtual assistants and to generate marketing content, among other uses. Target, Walmart and Best Buy this year announced plans to launch AI-powered tools to enhance the brick-and-mortar experience, especially for employees. Amazon just unveiled a new suite of AI models that could help accelerate tools like its e-commerce chatbot Rufus.

“The transformative nature of GenAI is helping us accelerate the rate of innovation across our operations, and we’re excited about the role these new tools and applications will play in driving growth,” Target’s chief innovation officer Brett Craig said in a statement in June.

A Salesforce and Retail AI Council survey of retailers in multiple countries conducted at the end of 2023 found that 20% of retailers had rolled out generative AI technology, with most others at least exploring it, if not beginning implementation. Just over 80% of retailers had an AI budget, the survey found, with the top functions for generative AI being customer service, marketing and store operations.

“These new gen AI-powered capabilities further enhance our commitment to deliver better, more personalized experiences to our customers by unlocking the power of people,” Brian Tilzer, Best Buy’s chief digital analytics and technology officer, said in a statement when the retailer announced partnerships with Accenture and Google to create and scale new AI tools, per Retail Dive.

In August, John Furner, president and CEO of Walmart U.S., said generative AI has helped the company populate the attributes and characteristics of hundreds of millions of items on its website and that it would have taken 100 times longer to do this manually. “We’re able to match the catalog to their intent in a much more effective way because the detail of each item and the product display pages has gotten so much better,” Furner said in an earnings call.

“What brands are looking for is a way to do the most difficult or menial parts of the job better,” said Amit Jhawar, CEO of SMS marketing platform Attentive and former general manager of Venmo. Sending tailored text messages to individual customers is one instance where doing so would be difficult, if not impossible, and require thousands of workers. The Attentive platform now has AI features that can text specific customers when particular products they have been looking at go on sale, for example.

According to Jhawar, brands using Attentive’s AI features have seen their revenue growth rate double. “A lot of people are trying to save time and cut costs with AI. That’s not what we’re doing,” he said. “We’re trying to make these brands more revenue; we’re trying to build bespoke shopping experiences for each consumer.” Jhawar said more than half of the brands Attentive works with now use its AI products, a double-digit percentage increase from 2023.

Marius Laza, chief customer officer of chatbot provider Tidio, said because more people are using tools like ChatGPT in their personal lives, it has been easier this year to sell people on its potential. “People came in and they knew what it can do,” Laza said. “They trust the technology a bit more.”

Laza said the company has had to temper expectations from companies wanting to completely automate chat conversations on their websites, whereas, in 2023, they were more hesitant to do so. “Realistically, there’s always going to be some type of tier-two request that needs to be escalated,” Laza said, adding that most people think they have a good FAQ and a good knowledge base to help inform the AI, “but they almost never do.”

In DeMeyere’s opinion, generative AI could lead to a world where every customer gets a completely unique shopping experience geared to resonate with them, specifically, from email subject lines to push notifications and images on the homepage. He said ThredUp could become essentially a personal thrift store for each of its customers.

“We knew that this will transform e-commerce in some way,” he said. “If we don’t figure out what it means for us, someone else is going to, and then we’re going to be behind.”

https://www.modernretail.co/technology/in-2024-retailers-like-walmart-thredup-used-generative-ai-to-make-shopping-more-personal

Source: Fast Company, Adele Peters
Photo: Amtrak

Taking the train from D.C. to Boston is about to get nicer—and a little faster.

Earlier this year, if you happened to be standing at a train station in New Jersey at a certain time of night, you might have seen a sleek new high-speed Acela zip by. The trains, which did 900 test runs between January and August, are expected to start commercial service on Amtrak’s Northeast Corridor line next spring.

They’re designed to be a better ride than the existing two-decade-old Acela trains, which carried nearly three million passengers last year. The new trains are quieter and designed to minimize vibration, so the ride feels smoother. They weigh less and are more aerodynamic; though the old trains are also electric, the new version uses less electricity to run. The first trains went into service in 2000, when cellphones were relatively rare; the new trains will have USB outlets (and regular outlets) at each seat. Winged headrests at each seat will offer a little privacy and prevent your neighbor from falling asleep on your shoulder. The trains will have an extra car, to carry around 25% more passengers, and will run more often. They’ll also be faster, at up to 160 miles an hour. The current trains are limited to 150 miles an hour.

The caveat: 160 miles an hour is still much slower than high-speed rail in other countries. In China, the Shanghai Maglev can travel at up to 285 miles per hour. Deutsche Bahn runs trains in Germany at up to 217 miles per hour. France’s TGV can run at nearly 200 miles an hour, with faster trains coming out next year. India is planning a new high-speed rail line that will also travel around 200 miles an hour, with help from Japan, where bullet trains go as fast.

Amtrak is limited by aging train tracks and curves along the route. “In most places in the world, when you’re doing high-speed rail, you’re designing the tracks and building the system at the same time that you’re building the trains,” says Dani Simons, VP of communications for Alstom, the French company that designed the new Acela trains and is building them in upstate New York. “Those tracks are generally designed to be very straight, very few curves. You’re not sharing tracks with other types of trains. Here in the Northeast Corridor, Amtrak had a really interesting and bold vision to bring high-speed trains to [an area] which had basically none of those qualities.”

Alstom, which also designed France’s high-speed trains, engineered Amtrak’s new trains to travel at up to 186 miles an hour—though that won’t be possible on this route. But new tilting technology means that the trains can better lean into curves, shaving some time off the journey. Amtrak also plans to upgrade some of the slowest parts of the route, like the B&P tunnel in Baltimore, which was originally built during the Civil War, so that trains will eventually go a little faster in those spots. (Right now, that tunnel is limited to 30 miles an hour.)

Building a whole new track in the densely built Northeast is probably unlikely at this point. But new, truly fast routes are more feasible in other parts of the country.

Brightline is working on a high-speed rail line between Las Vegas and Southern California, with plans for trains that could travel at 186 miles an hour. (California’s long-delayed high-speed rail project is also under construction, though it’s possible that Trump could set the project back.) And Amtrak has proposed building a new high-speed line between Houston and Dallas. “Those are two major metropolitan cities that are a little too far to drive, a little too short to fly,” says Amtrak spokesperson Jason Abrams. The 240-mile route, which is fairly straight, would take less than 90 minutes.

Catching up with the rest of the world will take more investment. “A lot of this is historical in the sense that in the 1950s, America decided to get more into highways and roads and planes [instead of] trains, as opposed to counterparts in Europe and Asia,” says Abrams. Over the last half-century, the U.S. has invested $120 billion in rail, he says. (Around half of that came from the Bipartisan Infrastructure Law in the past few years.) Since 2000, the U.S. invested $1.3 trillion in highways. Europe invested a trillion dollars in rail over the last two decades.

Faster trains, of course, could help better compete with carbon-intensive driving or flying. The climate benefit is especially big for the Acela trains, which run on electricity. The current trains reduce emissions compared to flying by 73%, and have 83% lower emissions than driving. The new trains will have a carbon footprint that’s even lower.

ABOUT THE AUTHOR

Adele Peters is a senior writer at Fast Company who focuses on solutions to climate change and other global challenges, interviewing leaders from Al Gore and Bill Gates to emerging climate tech entrepreneurs like Mary Yap.. She contributed to the bestselling book Worldchanging: A User’s Guide for the 21st Century and a new book from Harvard’s Joint Center for Housing Studies called State of Housing Design 2023.

https://www.fastcompany.com/91242054/amtraks-sleek-new-high-speed-electric-trains-are-coming-next-spring