Google announced its widely anticipated Gemini 3 model Tuesday. By many key metrics, it appears to be more capable than the other big generative AI models on the market.
In a show of confidence in the performance (and safety) of the new model, Google is making one variant of GeminiGemini 3 Proavailable to everyone via the Gemini app starting now. Its also making the same model a part of its core search service for subscribers.
The new model topped the scores of the much-cited LMArena benchmark, a crowdsourced preference of various top models based on head-to-head responses to identical prompts. In the super-difficult Humanitys Last Exam benchmark test, which measured reasoning and knowledge, the Gemini 3 Pro scored 37.4% compared to GPT-5 Pros 31.6%. Gemini 3 also topped a range of other benchmarks measuring everything from reasoning to academic knowledge to math to tool use and agent functions.
Gemini has been a multimodal model from the start, meaning that it can understand and reason about not just language, but images, audio, video, and codeall at the same time. This capability has been steadily improving since the first Gemini, and Gemini 3 reached state-of-the-art performance on the MMMU-Pro benchmark, which measures how well a model handles college-level and professional-level reasoning across text and images. It also topped the Video-MMMU benchmark, which measures the ability to reason over details of video footage. For example, the Gemini model might ingest a number of YouTube videos, then create a set of flashcards based on what it learned.
Gemini also scored high on its ability to create computer code. Thats why it was a good time for the company to launch a new Cursor-like coding agent called Antigravity. Software development has proven to be among the first business functions in which generative AI has had a measurably positive impact.
Benchmarks are telling, but as the response to OpenAIs GPT-5.1 showed, the feel or personality of a model matters to users (many users thought GPT-5 was a dramatic personality downgrade from GPT-4o). Google DeepMind CEO Demis Hassabis seemed to acknowledge this in a tweet Tuesday. [B]eyond the benchmarks its been by far my favorite model to use for its style and depth, and what it can do to help with everyday tasks. Of course users will have their own say about Gemini 3s communication style, and how well it adapts to user preferences and work habits.
With the release of Googles third-generation generative AI model, its a good time to look at the wider context of the race to build the dominant AI models of the 21st century. The contest, remember, is only a few years old. So far, OpenAIs models have spent the most time atop the benchmark rankings, and, on the strength of ChatGPT, have garnered most of the attention of all the players in the emerging AI industry.
History on its side?
From the start, Google has enjoyed some distinct advantages. Its been investing in AI talent and research for decades, starting long before OpenAI became a company in 2015. It began developing machine learning techniques for understanding search intent, defining page rank, and for placing ads as far back as 2001. It bought London-based AI research lab DeepMind back in 2014, and DeepMind has been responsible for some of Googles biggest AI accomplishments (AlphaGo, AlphaFold, Gemini models).
The big research breakthroughs that enabled the current wave of generative AI models took place at Google. In 2017, Google researchers invented the transformer language model architecture that allowed LLMs to learn much more from their training data than earlier language models. The following year Google used the transformer architecture to build its BERT language model, which led directly to the GPT models that power ChatGPT. In fact, the search giant developed an AI chatbot well before OpenAI did, but was conflicted about releasing it or infusing it into its other products because of legal and business model concerns.
All the data
Google has access to more and better-quality training data than any other AI company. Its been indexing most of the information on the web since 1998. It also owns huge amounts of information such as local business data, mapping data, and customer reviews, which can be used to train AI models or augment their output (within search results, for example).
Generative models are just now gaining the ability to learn about the world from video footage in the same way that models learn from large amounts of text. With YouTube, Google has access to mountains of it, and its AI models could gain an increasing intelligence advantage by training on it.
As AI begins to manage more and more of our personal and work tasks, Googles advantages in experience, talent, and data and other resources may help sustain Geminis state-of-the-art status and overall functionality in the years to come.
High stakes
This is more than about which company can sell the most API access to its models or subscriptions to a chatbot. As models like Gemini, Claude, and GPT-5 may eventually become smarter, perhaps far smarter, than humans at almost any task. The company with the models that reaches that level, also called artificial general intelligence (AGI) may dominate the marketplace for consumer and business AI in the same way Google has dominated search in the first decades of this century. With tech companies already spending hundreds of billions to build the infrastructure for their AI businesses, the pressure is mounting to push harder and faster on the development of new generations of AI models.
AI is bringing voice to the forefront of brand interactions. Smarter AI means we can talk to our technologyLLMs, software, phones, cars, fridges, and even banking apps. The novel part is this: Our technology is now talking back, and convincingly so. Brands are catching on, and the smart ones know that voice isnt just functional, it will form a core part of the brand identity itself.
Voice will be the next frontier of branding. And not metaphorically. A brands literal voicethe voice(s) used for advertising, on their website, and now, in interactive AI-based conversations with customersis becoming just as ownable as elements of a visual identity. But standing out wont come from just using voice tech alone. To cut through the noise, brands will need a voice thats authentic, distinct, and is uniquely associated with their brand.
The biggest brands already understand this. Theres a reason the most memorable brands choose to use the same voice actor across marketing campaigns, sometimes even across years: Consistency builds memorability, recognition, and trust. With voice AI, the opportunity for consistency and impact is even greater, and brands that embrace it will set themselves apart from the rest.
TURN CUSTOMER TOUCHPOINTS INTO BRANDED EXPERIENCES
The real gold in voice AI is its ability to provide both one-to-one and one-to-many communication at scale. AI is empowering brands to automate interactions across more customer touchpoints than ever before, including sales support, call center automations, and personalized ads, to name a few. As these channels incorporate voice AI, the need for consistency grows, making a singular, distinct voice more critical than ever.
With voice AI, brands can hold a million individual conversations at once while maintaining both continuity and a personal touch. In customer support, an AI-powered agent can provide instant answers and even act via voice. That same voice can guide them through a product tutorial, help pay a phone bill, or introduce your brand to customers in an ad.
Thats the beauty of voice AI as a brand asset: One voice can now efficiently scale, enabling a whole new level of brand cohesion across multiple interactions. Customers value predictability, and a consistent, trusted, and recognizable voice can really drive home that brand memorability and distinction.
SECURE A MEMORABLE VOICE THATS EXCLUSIVELY YOURS
With technology moving so fast, theres no shortage of ready-to-go AI voices. But the convenience of these voices doesnt guarantee exclusivity, and in branding, distinction is everything.
The problem with 100% synthetic AI voicesvoices entirely created with AI, with no real human in the loopis threefold:
They may become unavailable.
They are often forgettable.
They are rarely exclusive to the user.
As vendors update their library or licenses expire, the voice youve been using to represent your brand could change, or even completely disappear. Even if it doesnt, chances are: Other brands and creators are using that same off-the-shelf voice, erasing any sense of individuality. As a brand, youll want at least some exclusivity for your AI voice, so you dont end up sharing it with a competitor.
The reality is, the best AI voice clones come from real humans with the best voices: voice actors. You can hear a tangible difference between a synthetic AI voice and an AI voice cloned from a skilled voice talent. Done right, the one-to-one voice clone is higher quality than any synthetic voicenot only in its realism, but in its emotional nuance, uniqueness, and overall human quality.
Licensing a professional voice also gives you greater control over creative direction to ensure the pronunciation of brand names and technical terms is correct. Licensed voices also offer customizable licensing suited to your specific needs, securing long-term consistency, exclusivity, and greater legal protections. Its the difference between borrowing something generic and curating a voice experience that is yours.
The best, most successful branded voices in the market today are distinct and emotive. Customers wont remember an AI chatbot with a friendly middle-aged female voice, but they will remember a voice with personalityone that feels alive, intentional, and unmistakably part of the brand.
Thats the future: Voice as a distinguishable brand asset, just like a logo. And by working with real humans to create a unique AI voice, youll secure something competitors cant copy: A voice that is exclusively, recognizably, and enduringly yours.
Jay OConnor is CEO of Voices.com.
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.”
