Ransomware doesnt knock on the front door. It sneaks in quietly, and by the time you notice, the damage is already done. Backups, replication, and cloud storage help recover from ransomware, but when it strikes, these products may not be enough. You copy your data and ensure copies are recoverable when needed.
Replication is often viewed as the gold standard of protection. It is fast, efficient, and seems like an easy answer. Two common types of replication are in use today.
The first is physical to physical. This is when data is copied from one physical device to another, usually at a remote location. The second is physical to virtual. This is when data is copied from a local physical device to a virtual device in the cloud, commonly managed by a backup vendor.
Both replication types can be useful and offer advantages, including uninterrupted service, reduced potential data loss, and data redundancy. But replication has limitations.
When ransomware strikes
When ransomware hits a server, the infection can spread fast. If replication is active, then corrupted or encrypted data may be copied to the secondary device. Both the original and secondary devices now contain bad data. Instead of serving as a safety net, replication can become a trap locking both environments into a compromised state.
Replication can also be complex to set up and maintain, requiring skilled staff. Not every organization has the time, budget, or expertise to set up and maintain a replicated environment.
Replicating to a vendors cloud can be expensive. You pay for the storage, and often for recovery and ongoing usage. Plus, if your original server goes down and you need to switch to the secondary server, you still need to rebuild the original serverreinstalling the operating system, reapplying patches, and restoring the previous configuration. This can take time depending on the environment.
Where does this leave us? Should we just throw replication out the window? No, replication has its place. It can solve certain problems, especially when the risk of downtime outweighs the maintenance costs. But replication is not a cure-all. It should not be viewed as the primary recovery tool, especially against ransomware.
Ask if you’re prepared
Some questions can help you determine if you are ready for a cyberattack. Replication is a great tool, but ransomware can often expose its weaknesses:
Have you thought about what would happen if ransomed data spread across your replicated systems?
Do you know how long it would take to rebuild an original device if you had to switch over?
Have you tested your recovery process end-to-end, not just the replication part?
Do you understand the true cost of your replication service, including the hidden recovery fees?
Look beyond replication
Replication is valuable, but it shouldnt be the primary mechanism for recovery from a cyberattack. Replication comes with costs and complexity, and doesnt replace the need for a recovery strategy. So consider replication a tool in the toolbox, not the entire strategy.
You need a way to quickly restore an infected device to a clean statewithout worrying whether the compromised data has spread across your replicated environment. Or whether the recovery will cost more than the attack.
Users sometimes download files locally or store critical data outside of the replicated environment. A complete recovery strategy must include both servers and workstations to ensure quick recovery, regardless of which devices become compromised.
When considering ransomware recovery, explore solutions that provide resilience and data integrity, and enable fast recovery when your data is compromised. Instant recovery is achievable with solutions designed to recover from ransomware and other cyber threats.Elisha Riedlinger is the COO at NeuShield.
The cryptocurrency market is continuing to tumble as investors worry about risky assets, an AI and tech bubble, and a roughly 50% likelihood of the Federal Reserve cutting interest rates.
Closely watched digital asset XRP (XRP-USD) has fallen to $2.13 per token, a 26.55% drop from three months ago.
It previously hit a high of $3.65 in July, but the cryptocurrency has been trending significantly downwards since early October. This fall keeps XRP below the critical support/resistance level of $2.20.
XRP ETFs fail to boost price
There were moments of hope that the price would rebound with the recent launch of three XRP exchange-traded funds (ETFs). However, those hopes were soon dashed.
Take Canary XRP ETF, from Canary Capital, which launched on November 13. The fund (XRPC) opened at $26.63 that first day but has since fallen 10.85%. Binance News reports that “whales” sold 200 million XRP in the 48 hours following.
Blockchain company Ripple Labs is traditionally the largest owner of XRP, which is the native token of the XRP Ledger.
‘Profit-taking’ and the broader crypto slump
XRP is following a similar downward pattern to other cryptocurrencies, such as Bitcoin, the worlds most popular cryptocurrency.
Its price (BTC) also began to fall in early October and has made a sharp decline since early November. This week, it experienced a so-called death cross, which is when an asset’s short-term price momentum falls below its long-term trends.
As of publishing, Bitcoin sits at $91,577, a 13.26% drop from six months ago and an 18.12% drop from just one month ago.
The selloff is a confluence of profit-taking by LTHs [longtime holders], institutional outflows, macro uncertainty, and leveraged longs getting wiped out, Jake Kennis, senior research analyst at Nansen, said in a statement to CoinDesk this week. Profit-taking occurs when investors cash out to ensure a higher price, rather than hold a potentially declining asset.
While Bitcoin is still significantly up from a low of $74,436 in April, its gains for 2025 have been completely wiped out. It’s down roughly 2.14% year to date.
Every industry eventually reaches its productivity era. Manufacturing had automation. Finance had algorithmic trading. Today, real estate is stepping into its own transformation: the age of intelligent decision making.
Ive seen firsthand how investors are reimagining their operations. For decades, property investment was managed with clipboards, paper checks, and late-night phone calls. It left investors buried in minutiae.
Now, just as modern supply chains run on smart logistics, real estate is running on smart systems that streamline everything from payments to tenant communications. The result? A shift away from chasing down tasks and toward making wise, future-oriented decisions.
FROM ENDLESS TO-DO LISTS TO INTELLIGENT DEFAULTS
Smart investors are creating portfolios that think ahead. A good example of this is making sure lease renewals no longer catch the investors by surprise. To remedy this, property owners are using systems that automatically send themselves lease expiration reminders at critical times (whether that is 90, 60, 30, or 7 days beforehand). Those reminders keep each of their properties on schedule, whether the plan is to renew a great resident or list the property for new interest.
This kind of intelligent default has become a hallmark of modern operations. Routine communication, recurring tasks, and renewal cycles all happen on precise schedules set by the investor. The technology follows their logic, not the other way around. These built-in prompts and automated workflows turn repetitive management into proactive planning. Investors stay focused on growth, while the system quietly handles the details in the background.
KEEP CONTROL WHILE SCALING SMART
As portfolios expand, control becomes the defining advantage. The most sophisticated investors are scaling through rules-based automation by adopting a digital infrastructure that mirrors their judgment across every property.
Ive watched how this works in practice. Investors create specific rules that reflect their personal standards: how to screen residents, when to send payment reminders, how to communicate about maintenance. Once those rules are set, the system enforces them automatically and consistently.
Each property operates according to the investors playbook, giving them confidence that every detail aligns with their approach. That way, automating doesnt mean giving up control. Instead, the investors expertise becomes codified and applied across the portfolio. This is how smart growth happens.
REAL ESTATES PRODUCTIVITY ERA
A new rhythm is emerging in real estate, as smart systems generate time, and time generates smarter decisions. Investors who once spent evenings chasing paperwork now spend that time analyzing portfolio trends, comparing rent performance across markets, and identifying when to refinance or expand.
This productivity cycle turns operational gains into strategic insight. Each automation saves a few minutes, each saved hour leads to a better decision, and each good decision strengthens long-term performance. As more independent real estate investors adopt intelligent systems, they are operating with the same clarity and responsiveness once limited to large institutional firms, only now at the scale of individual portfolios.
SMARTER SYSTEMS LEAD TO HAPPIER HOMES
When operations become intelligent, the ripple effect reaches residents. Payments are made seamlessly through mobile tools. Maintenance requests route directly to the right vendor. Renewals are handled early and clearly, reducing last-minute stress for everyone involved.
For example, RentRedis internal data shows that when residents use features like autopay and credit reporting, on-time payments increase to 99% and by 13 points, respectively. These tools simplify the payment process while also supporting renters financial wellness by helping them stay current on rent while building stronger credit scores. When convenience meets incentive, the result is a healthier financial ecosystem for both residents and investors.
The smartest investors understand that streamlined operations lead to stronger tenant relationships. Happy renters renew leases more often, take better care of their homes, and create stability that fuels long-term returns. Intelligent systems make that balance possible, because they are efficient for investors and convenient for those who call their properties home.
MEET THE MOMENT OF INFLECTION
Real estate is now at the same inflection point that other industries reached when intelligence and automation converged. Smart investors are already leading this transformation, by building portfolios that run smoothly with insight, structure, and foresight.
They manage by design, using systems intentionally built to reflect their standards and priorities. Each workflow, rule, and automation represents their expertise in action. The business runs with purpose, clarity, and consistency because every element has been designed to anticipate needs, maintain performance, and create stability.
This design-led approach turns management into strategic execution. Investors operate within systems that think ahead, ensure precision, and keep portfolios moving in sync with their goals. This is what the age of intelligent real estate looks like: investors in control, operations running with clarity, and homes that reflect the benefit of smarter thinking.
FINAL THOUGHTS
The next generation of savvy real estate investors has already arrived. They have built operations that are thoughtful, predictive, and scalable. Their systems manage the details, their data fuels their strategy, and their decisions define a new benchmark for success.
The age of intelligent real estate is not a future visionit is already here, reshaping how the most forward-thinking investors grow, manage, and thrive. And as more industries adopt intelligence as their foundation, real estate stands as proof that when technology aligns with human insight, innovation becomes progress.
Ryan Barone is cofounder and CEO of RentRedi.
When I was a kid, my favorite place in the world was hunched over a sewing machine. Id cut up old jeans, hand-stitch fabric scraps into new outfits, and dream of someday seeing my clothes walk a runway. My notebooks were full of fashion drawings. Somewhere in my teens, that dream slipped quietly into the background. Life pulled me in a different direction.
But this year, thanks to AI, I finally staged my first runway show at New York Fashion Week.
Okay, not at the literal Fashion Week runways in Manhattan but on social media where people are scrolling for Fashion Week content. And the wild part? I pulled it together in one Friday night using my own AI-powered fashion brand, yanabanana.
The tech stack behind the catwalk
The show was called The Stockholm Archipelago Collection, inspired by a trip I took to Yasuragi, a Japanese-style spa perched on the water outside Stockholm. Architectural shapes, blue kimonos, and tall pines by the water were my mental mood board as I was designing my collection.
Heres how I translated inspiration into a digital runway:
Sketch to photo: I started with a rough sketch of each look. Using Google’s Nano Banana image generation model, I transformed my doodles into photos. Sometimes I generated two photos (a start and end scene) that would ultimately create a more interesting runway moment.
Models on the runway: Through prompt engineering, I iterated until all my looks walked the same runway that I had decorated with my photos of the water view from Yasuragi.
Static to cinematic: I turned the images into short clips with Midjourneys video model. It worked but Ill be experimenting with different video models next season. Runway fluidity is tricky!
Custom soundtrack: Every show needs a vibe, so I used Suno to generate an original Scandinavian inspired track to set the pace.
Cut & polish: Finally, I stitched it all together in iMovie, as old-school as it gets in the age of AI.
The result? A minute-long AI-powered runway film that could almost pass for an indie cut of a Fashion Week show.
AI is the new sewing machine
What I love about this process is that AI collapsed the barrier between imagination and execution. Ten-year-old me could only dream of sourcing fabrics, hiring models, and booking a venue. Today all I need is a sketch, a stack of AI models to create virtual human models, and a little curiosity. And yet, the story didnt stop at the digital runway.
From sketch to closet
At one point, I even thought about building a platform where fashion designers could sketch with AI and then manufacture their garments. That idea simmered until I stumbled on Flair, an early- stage startup already doing exactly that. I joined one of their sessions with a roomful of fashion designers during San Francisco Design Week this spring. The format was like an AI version of Project Runway. Everyone created some designs, and whichever one got the most votes on their platform over the next week would be brought to life. Mine won. I sent in my measurements, and last week a package arrived. Inside was a dress that had started as a doodle on my notebook, passed through Flairs AI workflow, and emerged as a real garment stitched together in the physical world. Slipping it on for the first time was magic. It was the same rush I felt as a kid cutting up old jeans. Except this time the runway wasnt just in my imagination. It was hanging in my closet.
The bigger picture
For me, yanabanana isnt about building a traditional fashion house. Its about asking what does a fashion brand born in the age of AI even look like? Maybe it doesnt need to produce clothes at all. Maybe its runways live on Instagram, soundtracked by generative beats, designed with prompts instead of pins. And maybe, sometimes, those designs make the leap from pixels to fabric. And maybe thats exactly what makes it fashion-forward.
Yana Welinder is Head of AI at Amplitude. She was CEO and founder of Kraftful (recently acquired by Amplitude).
Today, retail giant Target Corporation (NYSE: TGT) reported its third-quarter fiscal 2025 earnings. Unfortunately, for the company and its investors, the results were a continuation of what Target has been seeing for years now: declining sales.
Heres what you need to know about Targets Q3 and the impact the earnings are having on the companys stock price today.
Targets Q3 2025 at a glance
Heres what the big box retailer reported for its Q3 2025:
Net sales: $25.3 billion (down 1.4% from the same period in 2024)
Adjusted earnings per share (EPS): $1.78 (down from $1.85 in the same period in 2024)
Operating income: $948 million (down 18.9%)
Net earnings: $689 million (down 19.3%)
To put those first two all-important metrics into perspective, net sales came in below what analysts were expecting, but the companys adjusted earnings per share came in slightly above.
As CNBC notes, LSEG analysts expected Target to post revenue of $25.32 billion and an adjusted EPS of $1.72.
One bright spot in Targets Q3 results was digital comparable sales, which increased 2.4%.
Announcing the companys Q3 2025 earnings, Targets incoming CEO, Michael Fiddelke, who takes the helm in February, said, “Thanks to the incredible work and dedication of the Target team, our third quarter performance was in line with our expectations, despite multiple challenges continuing to face our business.
Targets sales woes continue
What are those “multiple challenges”?
Most broadly, Target has seen stagnant or declining quarterly sales for years now. Some of those sales woes are driven by factors not unique to Target.
For several years now, retailers of all stripes have been seeing customers who are more cautious about how and where they spend their discretionary dollars. This caution has largely been spurred by inflationary pressures leading to rising cost-of-living expenses.
The company, like most retailers, is also facing significant competition from other big-box giants, including Walmart, as well as from online retailers like Amazon and, in more recent years, Temu and Shein.
However, several factors unique to Target have also impacted its sales for quite some time.
As Fast Company reported in May, customers had been complaining about messier layouts, long lines, and understaffed stores. This had led to a notable decline in customer service in many customers eyes.
Finally, earlier this year, Target rolled back some of its DEI initiatives after Trump came to power. This prompted backlash and a boycott from many Target customers. Target has previously said this backlash impacted sales.
All eyes on the holiday quarterand TGT stock
Despite the sales decline in Q3, Target maintained its outlook for its current Q4, which includes the all-important holiday period.
Yet, thats not exactly a good thing. Target had previously forecast that it expects its Q4 to see a low single-digit sales decline, and now it has confirmed that it still expects that decline (but at least, the company might argue, the decline isnt forecast to be any worse).
What Target did adjust was its full fiscal 2025 forecast. Target previously said it had expected adjusted earnings per share for the year to come in at between $7 to $9. But now the company says it expects adjusted EPS for fiscal 2025 to be between $7 and $8.
Targets stock reacted about as well as you would expect. As of this writing, TGT shares are currently trading down about 2.97% to $85.90 per share in premarket.
The companys stock price has had a rough 2025.
Since the year began, TGT shares have declined more than 34% as of yesterdays closing price of $88.53. Looking back over the past 12 months, things are even worse. During that time, TGT shares have declined more than 43% as of yesterdays close.
Across nearly four decades as a teacher, principal, superintendent, funder, and now leader of a large education nonprofit organization, the experience that most shaped my view of learning wasnt a grand reform or a shiny new program. It was a Friday physics lab in Brooklyn. My students predicted a graph that couldnt exista vertical line for velocity and time. What followed was confusion, debate, trial, and error. And then discovery: Velocity requires both displacement and time. That brief struggle taught me, the teacher at the time, more about how learning really happens than any policy memo ever has.
That moment endures because it represents what school should unlock every day: inquiry, persistence, and the joy of figuring something out yourself.
Too often, students still move through school executing a recipe of steps without understanding ideas. In math, science, history, and English language arts, they follow the recipe and miss the point. That approach may be tidy, but its not transformative. It shortchanges imagination, curiosity, and the a-ha! moments that make knowledge durable.
HOW TO EMPOWER STUDENTS
I believe that learning is only powerful if it combines agency, purpose, curiosity, and connection to empower students for the future. What does that mean? It means that learners should pursue knowledge through action. Through choice. And through voice. They should have opportunities to develop authentic and meaningful contributions. They should explore new ideas and experiences to better understand their world. And they should make connections between ideas, experiences, and people.
When students are allowed to experimentto wrestle productively and recover from mistakesthey dont just master content; they build the habits of mind that matter in life and work.
TECHNOLOGYS ROLE
Emerging technologies hold enormous potential to make these kinds of experiences more common. They help curate simulations, prompt inquiry, and scaffold experimentation. It can create new entry points for students to explore, revise, and connect their ideas. The little moments of technology matter, toolike a 90-second BrainPOP animation that unlocks a tough concept. An interactive that prompts a classroom debate. A quick, purposeful game that turns practice into understanding. These are the sparks that turn a lesson into learning.
Technology is not a recipe to follow; its a set of instruments to conduct. If we want learners who can think with and about AI, then classrooms must invite students to do what my Brooklyn High School physics class did: predict, test, argue from evidence, and revise. This last part can demonstrate the evolution in a students thinking processes and how they can move through conceptual phases of understanding. This requires commitments like access and teacher expertise, as well as ensuring quality over quantity.
Im heartened to see some schools rising to meet this challenge, like the Ypsilanti Community High School in Michigan, with its new AI Lab.
The first-of-its-kind collaboration between the school district, leading tech companies, and nonprofits equips students with advanced tools for AI-powered learning. This includes processors designed to handle complex AI computations, audio-visual equipment, and 3D modeling software. The lab doesnt simply build AI literacy; it allows students to explore ideas that matter to them using advanced technology. At once, they gain hands-on experiences in emerging fields while also fostering a sense of creativity and innovation. The lab challenges them to think critically, pushes them to be creative, and strengthens their real-world problem-solving skills. These are the kinds of experiences we need to provide for students to prepare them for an AI-driven world.
LET STUDENTS LEARN THROUGH DOING
As we increasingly integrate AI in classrooms, students must be allowed to experiment and explore with it, to argue from evidence, to fail, to productively struggle. When done right, we see the right kind of noise. That means classrooms buzzing with questions. It includes debates. And students make lifelong connections.
I still remember that Brooklyn lab as if it were yesterday. Not because of the graph, but because of what it revealed: When students are trusted to do the intellectual heavy lifting, they surprise usand themselves. Our job is to design schools where discovery is not an accident, but the plan.
Jean-Claude Brizard is president and CEO of Digital Promise.
When Gabriela Flax left her corporate position managing 40 people to work on her career coaching businesses solo and moved from London to Sydney, the first thing she noticed was the silence. Without the constant movement, office hum, phones, and elevator dings, she says, she could finally bask in the quiet shed always craved.
But, she quickly realized, Oh, wow, there’s no one around me.
Flax, a career coach and founder of the newsletter Pivot School, says, I initially named my Substack No One’s in the Kitchen. I’d get off a work call super excited [because I] signed a new client . . . go to my kitchen to make a coffee, and no one’s there . . . just my dog looking back at me.
Running a business alone can feel liberating, but it can also come with a cost: a unique type of loneliness research suggests stems from acute uncertainty, resource constraints, responsibility, and time pressures. Online, subreddits, creator cohorts, and Discord groups brim with solo founders seeking to manage loneliness.
Loneliness is a mental health emergency in many cases, says Dr. Michael A. Freeman, a San Francisco-based psychiatrist who works exclusively with entrepreneurs.
Ironically perhaps, entrepreneurs often feel quite alone despite the fact that they have very large networks and communicate with lots of people every week, he explains, because those are largely transactional role relationships and solopreneurs, particularly, are pursuing a uniquely personal vision.
The loneliness can come from a lack of people, but it can also come from being the only person who holds your why so tightly, says Flax.
Identifying the loneliness loop
Particularly in a ventures early days, solopreneurs are living and breathing their new business, explain researchers Ashley Evenson, lecturer of creative enterprise at Goldsmiths, University of London and Beki Gowing, lecturer in fashion enterprise at London College of Fashion, who coauthored a study on entrepreneurial loneliness and burnout.
Loneliness, they say, [can be] the catalyst for other mental health difficulties, [eroding] decision-making, creativity, and emotional resilience. Social interactions slip, overwork rises, and a vicious and toxic cycle takes hold.
Diane Sullivan, business professor at the University of Dayton, calls this the regulatory loop of loneliness: Some founders respond by building connections and hobbies, while others withdraw, potentially making isolation worse .
In Flaxs case, she had to get creativedigital lunch invites via TikTok, long-form writing for other solo-foundersto cultivate relationships in her new role and city.
In what Flax describes as an eat what you kill field, solopreneurs can ill-afford to let loneliness derail their purpose. Heres how experts recommend fighting it.
Seek deep social experiences
Taking the first step to get out of a loneliness rut can feel awkward, but its key to make the effort to engage offline, even if it feels uncomfortable at first.
Juliana Schroeder, associate professor in the Management of Organizations group at Berkeley Haas, says one of the major instigators of loneliness is that people are trading deep social experiences for shallow social experiences.
Shallower social experiences are those that leverage AI connection, online engagement (particularly on social media platforms), and prioritize more superficial types of interactions, like short text-based conversations, for example, or group conversations over one-on-ones. Other potential connections, like talking with neighbors or disagreeing counterparts (say, talking across the political divide), are starting to disappear entirely, she says.
I suggest setting up environments that involve regular contact with community members, having recurring deep conversations to maintain and grow friendships, and stretching outside of your social comfort zone when any opportunity arises.
And it may not be as hard we imagine. We find that people’s psychological intuitions about some of these interactions are miscalibrated, she explains, and the awkwardness and depletion we anticipate is often overridden by the pleasantness of the interaction and how good both parties feel afterwards.
Flax recommends seeking connection outside of work: If you go to the gym at 3 p.m. on a Tuesday, or a coffee shop at 11 a.m. on a Thursday, not everyone in those spaces is going to be self-employed or building their own thing. But . . . chances are they might not have a [traditional] nine-to-five, she explains. It’s hard the first five times you [introduce yourself]. By time number six, you’re like, oh, whatever.
Quality over quantity
Preempting loneliness, at least initially, may also help proactively manage it, says Freeman, who recommends, engaging in a rich set of relationships that do not involve being a leader and ultimate decision-maker.
One of the founders I work with belongs to a football team that is part of a regional amateur league. He has many friends on the team, which he doesnt have to lead, and the camaraderie gives him a lot of social support, he adds.
Flax agrees, noting online cohorts, while full of a unanimous understanding of were all in this together, can lose meaningful connection when they exceed six to seven people. Dont just put us all in a room, she says, adding that breakout rooms on a Zoom call, for instance, help foster one-on-one connection.
Back to basics, away from the drawing board
Tim Michaelis, assistant professor in the department of psychology at North Carolina State University, founded and runs an annual Health in Entrepreneurship Conference.
Physical activity and sleep, he says, are two big recommendations, citing additional research that leisure activities can provide a way to detach from entrepreneurial work and improve venture performance.
Engaging with a local university or community college can help connect with like-minded people, feel less alone, and improve wellbeing, he adds. A small step could be going to watch a pitch competition or email a profesor to see if they need help with a guest lecture . . . Sometimes its a clear win-win.
Ultimately, its worth remembering that loneliness does not increase just because youre a team of one. Claude Fernet, an organizational behavior professor at Université du Québec Trois-Rivires, who studies job stressors in small and medium enterprises, raises an important point. Solo founders may actually have a bit of an advantage when it comes to job stressors and loneliness. Thats because “owner-managers” (or entrepreneurs with a small team of employees) feel the additional responsibility for others wellbeing and salary, leading to, the burden of shielding others from stress.
Still, he adds, That said, the psychological toll of isolation remains a significant concern in both cases.
Flax, meanwhile, recommends thinking of loneliness in stages.
Dont fight [it], she says, Because solitude is a part of building something meaningful . . . The day will come where the work you put into it is seen by others and you can create incredible community off the back of it.
Tiny fragments of microplasticsfrom clothes, car tires, packaging, and other sourcesslip through most water filters. But at a water treatment plant on the coast in Atlantic City, New Jersey, where plastic-filled wastewater would normally flow into the ocean, new technology has captured hundreds of millions of microplastic particles over the past year.
The technology, from a startup called PolyGone, can also clean microplastic out of lakes and rivers or treat wastewater at factories.
The startup spun out of research at Princeton, where the founders drew inspiration from aquatic plants that can naturally attract microplastic. The plants have fibrous roots coated in a hydrophobic gel that pulls in pollution. We managed to imitate the geometry and hydrophobility of the aquatic plant root, says cofounder Yidian Liu. It has a lot of unevenness on the surface that creates little cavities for smaller pollutants to be trapped inside.”
[Photo: PolyGone]
Wastewater treatment plants are a pathway for microplastic pollution to enter the ocean, which is now filled with trillions of particles. Most wastewater plants in the U.S. don’t use advanced treatment before releasing water back into nature. Of those that do, most existing filters only catch larger microplastic, between 1 and 5 millimeters. Tinier fragments, invisible to the naked eye, slip through. Another type of fine mesh filter in use in some plants captures more, but then the plastic just ends up in landfills.
In lab tests, PolyGone’s system captures 98% of microplastic. After the filters are full, they can be cleaned and reused. The plastic is concentrated and sent for reuse. In Atlantic City, where the company launched its first wastewater pilot in September 2024, it has already captured more than 520 million particles of microplastic, exceeding performance targets. The plastic goes to other companies: one that turns it into chemicals, another that is beginning to use it to make fuel.
[Photo: PolyGone]
The utility now plans to expand the pilot into a full-scale operational system. PolyGone, which recently raised a $4 million seed round of funding, designed a new filtration unit that automatically lowers itself into water and cleans itself on a schedule. The unit fits inside a standard shipping container, with all of the tech fully assembled inside so it can be deployed in a day at a wastewater plant.
The company also designed another version of the technology that fits into wastewater pipes at factories. The first pilot of that system just launched at an industrial plant in Dubai. “This system is a very simple way for them to plug and play and get rid of microplastic before the water goes into their effluent,” says Liu. Other manufacturers are also beginning to test the technology, including clothing companies working to cut microplastic pollution from synthetic fabric. Cost varies depending on the system, but ranges from roughly $15,000 to $50,000.
The technology is much less expensive than other advanced filtration, in part because the filter works passively to “dramatically reduce energy consumption compared to traditional advanced filtration systems that rely on high-pressure pumps,” Liu says. The open design avoids clogging, so it needs less maintenance. It also can easily be added to existing infrastructure, she says, rather than requiring expensive retrofits.
[Photo: PolyGone]
The tech can also be used directly in nature, and the company has tested a Roomba-like robot that filters water as it moves across a lake. But funding is harder to secure for this approach. There’s more demand for industrial use, especially from brands that are trying to tackle sustainability goals. And at wastewater treatment plants, some states may soon consider new regulations that would require better pollution filtering.
“California is leading on microplastic regulation,” says Liu. The state already requires microplastic testing in drinking water and is working on a new drinking water standard, though wastewater filtering isn’t mandated yet. “A huge reason is they don’t know what methodologies or systems are available for [wastewater plants] to quickly adopt for microplastic removal,” Liu says. “Our pilot is actually giving them a very good case study to understand okay, it is a problem that can be solved.”
AI models have a voracious appetite for data. Keeping up to date with information to present to users is a challenge. And so companies at the vanguard of AI appear to have hit on an answer: crawling the webconstantly.
But website owners increasingly dont want to give AI firms free rein. So theyre regaining control by cracking down on crawlers.
To do this, theyre using robots.txt, a file held on many websites that acts as a guide to how web crawlers are allowedor notto scrape their content. Originally designed as a signal to search engines as to whether a website wanted its pages to be indexed or not, it has gained increased importance in the AI era as some companies allegedly flout instructions.In a new study, Nicolas Steinacker-Olsztyn, a researcher at Saarland University and his colleagues analyzed how different websites treated robots.txtand whether there was a difference between sites measured as reputable versus not reputable, specifically in terms of whether or not they allowed crawling. For many AI companies, “It’s kind of a do now and ask for forgiveness later thing, Steinacker-Olsztyn says.In the study, more than 4,000 sites were checked for their responses to 63 different AI-related user agents, including GPTBot, ClaudeBot, CCBot, and Google-Extendedall of which are used by AI companies in their effort to soak up information.
The websites were then divided between reputable news outlets or misinformation sites, using ratings devised by Media Bias/Fact Check, an organization that categorizes news sources depending on their credibility and the factuality of their reporting.
Across all 4,000 sites assessed, around 60% of those deemed to be reputable news websites blocked at least one AI crawler from accessing their information; among misinformation sites, only 9.1% did so.
The average reputable site blocks more than 15 different AI agents through its robots.txt file. Misinformation sites, by contrast, tend not to shut out the crawlers at all.
The biggest takeaway is that the reputable news websites keep well up-to-date with the evolving ecosystem as it pertains to these major AI developers and their practices, Steinacker-Olsztyn says.
Over time, the gap between those who are willing to let bots crawl their sites and those that arent is widening. From September 2023 to May 2025, the proportion of platforms locking out crawlers increased from 23% to 60%, while the share of sites peddling misinformation stayed flat, the study found.
The result, Steinacker-Olsztyn says, is that less reputable content is being hoovered up by and then spat out of AI models used routinely by hundreds of millions of people. Increasingly these models are also being used simply for information retrieval, replacing traditionally used options such as search engines or Google, Steinacker-Olsztyn adds.
The conundrum over legitimate data
For AI models to stay up-to-date on current events, they are trained on reputable sites, which is exactly what these sites dont want.
The war over copyright and access to training data between AI companies and news sites is increasingly spilling into courtsThe New York Timess lawsuit against OpenAI, the makers of ChatGPT, for example, carried on into last week.
Those lawsuits are prompted by allegations that AI companies are illegally scraping data on news websites to act as regularly updated, ground-truth-based training data for the models powering their AI chatbots. In addition to litigating their disputes, reputable news websites are blocking AI crawlers.
Thats good for their businesses and rights. But Steinacker-Olsztyn is concerned about the broader impact. If reputable news is increasingly making this information unavailable, then this gives reason to believe this can affect the reliability of these models, he explains. Going forward, this is changing the percentage of legitimate data that they have access to.
In essence: It doesnt matter to an AI crawler whether its viewing The New York Times or a disinformation website run out of Hoboken. Theyre both training data, and if one is easier to access than the other, thats all that matters.
Not everyone is quite so certain about the negative impact of blocking crawlers. Felix Simon, a research fellow in AI and digital news at the University of Oxford-based Reuters Institute for the Study of Journalism, says he wasnt surprised to learn that sites trafficking in misinformation would want to be crawled, whereas traditional publishers have an incentive at this point to prevent such scraping. Some of these traditional publishers, he adds, still allow some scraping for a plethora of reasons.
Simon also cautions that just because misinformation sites are more likely to open their doors to AI crawlers, it doesnt necessarily mean that theyre polluting the information space as much as we may fear.
AI developers filter and weigh data at various points of the system training process and at inference time, he says. One would hope that by the same means by which the authors have been able to identify untrustworthy websites, AI developers would be able to filter out such data.
When the new year rolls around, many people will resolve to get in better shape. Last year, Americans poured $44.8 billion into the fitness industry, flocking to gyms and buying at-home fitness equipment. But it usually takes just two weeks for people to abandon their goals. Gym memberships go unused. Peloton bikes collect dust.
Researchers at the National Institutes of Health have found that amidst all the fitness options on the market, personal training tends to lead to better results for several reasons: It involves a personalized program, fits into the participant’s schedule, and requires being accountable to the trainer. But personal training is expensive, priced anywhere from $50 to $150 (or more) per hour for one-on-one sessions.
Ray, a new AI-powered fitness app, wants to offer all the benefits of a personal trainer for a fraction of the price. (In fact, the service is free for early users, but will eventually start charging a monthly fee.) When you open the app, an AI trainer that looks and sounds like a real person will guide you through a workout. The program will be customized to your goals, your bodily limitations, the equipment you have handy, and the amount of time you have.
And like a human trainer, Ray will observe your movements to help you improve your form and offer more challenging workouts as you improve. Ray will also follow up with you by text, like a real trainer, to see how the session went and to help schedule the next one.
Importantly, the technology is going to keep improving as more people use Ray and as AI evolves. “The conversation’s going to get more fluid; the vision is going to get better,” says Colin Raney, Ray’s cofounder. “We’re currently working on grunt recognition, to see if we can identify how the user is doing based on the sounds they’re making.”
[Photo: Ray]
Why Personal Training Works
Ray is the brainchild of Rich Miner, cofounder of Android, and Raney, an Ideo veteran and former CMO of PillPack. Over the years, both have relied on personal trainers and found them transformative. For Raney, it was clear that there were many aspects of working with a human being that could cultivate real behavior change. “I needed the accountability of not wanting to let my trainer down by not showing up,” he says. “Or tuning the workout to me if I had a bad day, or my back wasn’t feeling right, or if it looked like I was ready to push myself that day.”
Raney has thought about improving people’s health by changing their behavior. He helped build PillPack, which was designed to help people actually take their medicine by delivering it monthly in packets sorted by date and time. He believed it would be possible to get people to workout more frequently if they had access to the qualities of a personal trainer.
[Photo: Ray]
“Our thesis was that if you build the right behavioral loop, people will workout more regularly,” he says. This aligns with research that finds that people who relied on a personal trainer lost fat and built muscle, with a lower rate of injury, compared to people who worked out alone or in groups.
As Raney spoke with Miner about building a fitness tool, it became clear that AI technology was evolving to the point that it could mimic a personal trainer. Miner has been working on AI for decades, and has the patent to one of the first “wake words” for a voice-based personal assistant 35 years ago. “If you’re not a movie star or someone with a lot of money, you can’t afford to get that kind of personalized training,” he says. “But I realized that with agentic AI, you could actually start building virtual people who could watch you and talk to you naturally.”
[Photo: Ray]
Building an AI Native Tool
The fitness industry is working hard to incorporate technology into existing tools. Over the last decade, there’s been an explosion of tech-enabled machines, from Peloton and NordicTrack machines with screens that provide feedback about the workout, to weight-lifting machines like Mirror, Tempo, and Tonal that can help count your reps. Now, these companies are figuring out ways to incorporate AI into their systems, to better tailor workouts to the user.
Minor and Raney began building Ray two and a half years ago. What sets it apart from many other tools on the market is that it is built on AI, rather than simply retrofitting existing technology with AI. Ray is designed to approximate a real person that can interact with the user in a natural way.
“It adapts to you,” Minor says. “You don’t have to change a bunch of settings to make sure the workout is tailored to you. You can just say, “Ray, my shoulder’s hurting today.”
The technology is equipped with several cutting-edge AI technologies. It has natural language processing, to create real conversations with the user. It is able to observe the user across 35 different points, and has a machine learning algorithm that identifies your body movements. It is also equipped with an AI planner that helps you dynamically plan workouts based on the user and their workout history.
Ray has also incorporated a lot of highly specific data about personal training. The data is trained on the textbooks and manuals that personal trainers use to get qualified. Raney also became certified as a personal trainer to ensure the Ray experience is as realistic as possible. “Ray’s team has a huge amount of domain expertise,” he says. “We have a lot of knowledge about things like what constitutes a good workout and how to create a complete workout in a given amount of time.”
Raney believes that the seamlessness of the interaction is important because one big obstacle to behavioral change is decision fatigue. “Part of what holds people back is the mental load,” he says. “You have to decide when you will do the workout, and then make a lot of decisions about what exactly you’ll do and for how long. With a personal trainer, all you need to do is to show up at the agreed upon time and do the program.”
Minor believes that consumers will immediately see the difference between an AI-native fitness app, versus one that is back-solving into an existing system. He compares it to how companies started making mobile-first apps instead of just adapting their websites to mobile apps. “That’s when you got Instagram and Uber,” he says. “People rethought what an app could be if you didn’t have to rely on a legacy application. That’s what we’re trying to do with Ray.”
How An AI Personal Trainer is Different
Six months ago, Ray quietly launched on the app store, without any marketing. Thousands of users have already started using it. The founders say they wanted to see how users interacted with it and use this data to further train the AI.
When I tried it, I was impressed by how well the program adapted to my needs. In 20 minutes, I was able to do a range of exercises in my office without any equipment. As I did push-ups and jumping jacks, my Ray trainer was encouraging, telling me that I was on the right track. It also respected the fact that I hate burpees. (You can pick whether the trainer is supportive or a little more assertive, since different users respond to different approaches.)
[Photo: Ray]
But as with other agentic AI platforms I’ve used, I found that the interaction wasn’t perfectly seamless. I didn’t exactly feel like I was interacting with a human trainer; the AI trainer’s eyes seemed blank and unfocused. When I spoke, Ray would pause before responding to me in a way that made the conversation a little stilted.
Ray’s founders say that these aspects of the interactions will only get better as the more people use the platform and the AI itself improves. But for now, Ray didn’t feel human enough that I felt bad about letting it down if I didn’t show up for a workoutthe way I wold if I were working with a real person.
[Photo: Ray]
Miner acknowledges that an AI agent won’t provoke the same level of accountability that a human would, but he says that there are still benefits to creating an anthropomorphic app. “It’s more than about creating a sense of guilt about letting a person down,” he says. “A trainer guides you through what to do and they’re watching you as you workout, counting your reps and motivating you. Ray gives you all of that.”
And there are some ways that a virtual personal trainer is more convenient than a human one. You can do workouts at odd hours that a human may find objectionable. You don’t have to compete with the trainer’s other clients and you can cancel at the last minute. And then there’s the price.
Right now, Ray is free. But in the coming months, the founders will develop a pricing structure that is designed to be significantly less than the price of hiring a human personal trainer. Over time, the founders believe that Ray will begin to feel even more like the real thing.
“Ray has improved so much over the past six months since it’s launched,” says Raney. “It’s going to feel more and more real as time goes on.”
