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Every living organism, from the simplest microbe to the tallest tree, contains a library of genetic information refined by billions of years of evolution. This biological data dwarfs even our most advanced digital systems. Nature has been running the ultimate machine learning experiment since life began, optimizing solutions for survival, efficiency, and adaptation at a scale we’re only beginning to comprehend. What if, instead of replacing nature with machines, we could work with biological systems as collaborators? That’s the promise of modern biotechnology. Nearly two decades ago, my lab-mate Alvin and I set out on what many considered an impossible quest. We were PhD students at UC Berkeley with a radical idea: What if we could apply emerging biological tools to awaken dormant capabilities in living systems that could work alongside farmers? The fertilizer problem While 78% of the air we breathe is nitrogen, plants can’t access it directly. For millions of years, soil microbes solved this problem through nitrogen fixation, converting atmospheric nitrogen into plant food. But with the widespread use of synthetic fertilizers, many of these microbes went quiet. Their nitrogen-fixing abilities switched off. For years, farmers have been scattering fertilizer across their fields and hoping enough would reach their crops. Much of it didn’t. It washed into rivers and streams, creating dead zones in our waterways. Alvin and I imagined a different approach: a living system that could work in partnership with farmers. Microbes that would live at crop roots and respond dynamically to each plant’s needs. They would be tireless collaborators, optimizing nutrient delivery with a precision that comes from billions of years of co-evolution with plants. We collected soil samples from farms across the country, isolated promising microbes, and began gently reawakening their dormant nitrogen-fixing abilities and enhancing what nature had already perfected. One day in the lab as we peered into a test tube that contained a germinating corn seed. Our partner microbes had colonized the roots of the tiny plant, actively fixing nitrogen and sharing it with their host. That little plant, growing vigorously without any added fertilizer, was proof that we had succeeded. We hadn’t created artificial life. We had awakened life’s existing potential to work in harmony with human needs. Microbial revolution Today, these microbial partners work in the soil across millions of acres of farmland worldwide, helping farmers grow more food with less environmental impact. They’ve prevented over 1.3 million metric tons of greenhouse gas emissions since 2022 alone. They’re part of a quiet revolution happening at the intersection of biology and human ingenuity. This revolution extends far beyond agriculture. Scientists have discovered and enhanced microbes that naturally break down oil spills in marine environments, partnering with these organisms to accelerate ocean healing. Others have found bacteria that can digest plastic waste, turning pollution into harmless byproductsnot through harsh chemicals, but through the same processes that nature uses to recycle organic matter. Researchers are developing living materials that can sense damage and repair themselves, inspired by how our own bodies heal. In medicine, we’re seeing remarkable advances: bacteria that can detect cancer cells earlier than any machine, algae that produce life-saving drugs more efficiently than factories, and personalized therapies that work with our immune systems rather than against them. Each breakthrough represents a partnership between human creativity and nature’s tested solutions. A reimagined relationship with the living world Just as AI amplifies human intelligence by learning from the data we’ve created, this new biological age amplifies human capability by collaborating with the wisdom encoded in life itself. But unlike AI, which we build from scratch, we’re working with systems that have already solved many of our greatest challenges. We just need to learn their language. This is more than a technological shift; it’s a fundamental reimagining of our relationship with the living world. For the first time in history, we can have a true dialogue with naturenot to dominate or control, but to collaborate and co-create. The choice isn’t between nature and technology. It’s about recognizing that nature is the most sophisticated technology we’ve ever encountered. And we’re just beginning to learn how to work with it. In the biological realm, those partners have been here all along, waiting for us to learn their language. The future isn’t about making biology more machine-like. It’s about discovering that biology has always been more ingenious than any machine we could build. The real revolution isn’t in controlling life, but in joining it. Karsten Temme is chief innovation officer of Pivot Bio.
Category:
E-Commerce
So, weve all been there. Youre two paragraphs into a blog post. The headline was catchy enough, the intro kind of made sense, and now your eyes are glazing over. You read over a word, a blurb, a sentence that sounds vaguely all-too-familiar and now youre wondering, Wait…did a human even write this? Odds are, youre not imagining it. AI-generated content is everywhere. It is impossible to escape. While it’s efficient, especially for meeting summaries and article recaps, you and I know the best content is the content that feels particularly human. When you spend your days working with AI (and creating comprehensive AI training for your team), you quickly start seeing how its beginning to give itself away. Here’s how to spot AI writing before you waste another five minutes of your life reading machine-generated clickbait. 1. It reads like someone trying to win an argument at a networking event. If every paragraph feels like its trying to make a strong point without actually saying anything meaningful, youre probably in AI territory. Look out for generic phrases like in todays fast-paced world or leveraging innovative strategies. Ive read these phrases so often that it occasionally feels right to use them as filler, like an SAT tutor that teaches your kid three big, impressive terms to use to crush the written portion of the test. Ultimately, this is the biggest red flag that youre reading AI-generated content. 2. Theres 0% personality and 100% too much structure. AI content often follows a painfully clean format: intro, subheads, conclusion. The content might include some big words, but its not fooling anyone. It reads like it went to school and graduated with honors, but never worked a day in the real world. Great for a college essay, not so realistic (nor creative) beyond that. Theres no strong voice, no edgejust perfectly average takes. On this note, Im seriously considering creating a support group for copywriters and marketers who embraced the em dash long before AI came around. While its become popularized as an AI tell of a blog post or article, too often its a case of mistaken identity. Tread carefully. 3. Its bland, not very controversial. This flag can be a difficult one to spot in the moment, as its important to consider varying perspectives and points of view. AI doesnt like to ruffle feathers, so youll often find it hedging every single opinion. Itll say one thing, then immediately say the opposite to keep the peace. Look out for something along the lines of, While X has benefits, its important to consider the potential downsides of Y. Lets keep writing about things that may be controversial, with strong opinions and hot takes. When creatives are writing about a particular topic, and aiming to prove a point, it doesnt seem appropriate for them to include the counterargument. Right? Youre reading to gain insight and perspective about whatever topic is at hand, not ride the see-saw. 4. The conclusion is weirdly robotic pep talk. If the article wraps with something like, As we move into the future, embracing innovation will be key, congrats, youve hit AI bingo. These vague, motivational endings are a dead giveaway. The conclusion usually feels abrupt, as if AI knows its necessary for sentence structure but is not willing to spend the time on making it truly meaningful. I rarely see a real person sign off their blogs, newsletters, or other content with such blatant corporate optimism. 5. Your brain feels…untouched. Maybe the biggest tell is how it makes you feel (or not feel). Great writing sticks with you. Even a short blog post can inspire, surprise, or challenge you. But AI-written content, on the other hand, is like a lukewarm shower. Technically fine. Emotionally forgettable. I wouldnt go so far as to claim that specific words, key, crucial, robust, or comprehensive are always AI indicators, but it is true that most writing tools cant resist overusing their favorite buzzwords. Even ChatGPT refers to these words as its greatest hits list, so its no wonder that my mind is exhausted from seeing them in others writing. I use AI daily to optimize my workstreams, beat creative blocks, and sharpen my emails. And if I dont pay attention and refine my prompts, my results will be rampant with these tells. Dont believe me? Test it out using ChatGPT. With a little practice, youll soon be able to spot an AI-generated story from a mile away. Im not an AI-hater by any measure, but its been exhausting to find that every third article I read is missing that imperfect-but-human spark. If it feels too clean, too cautious, or like it was written in under 30 seconds, it probably was. Lisa Larson-Kelley is founder and CEO of Quantious.
Category:
E-Commerce
In todays unpredictable economy, more small and mid-sized businesses (SMBs) are feeling tight on time, resources, and bandwidth. Having the right tech in place can help; the past decade has seen an explosion of technology helping small businesses. The downside is that small businesses often need to juggle their data and attention between multiple apps, which is frustrating and expensive. Recent studies show 70% prefer comprehensive, all-in-one solutions that keep everything in one place. But where are these all-in-ones? Software companies have been struggling to create the ambitious all-in-one package because of the costs of building and supporting different types of software (e.g. invoicing, bill pay, accepting payments, accounting, customer marketing, payroll, and more). Thats where the embedded fintech model comes in. More tech companies are now working together to build better experiences, rather than going it alone. With embedded fintech, platforms can embed their tech into software and customize it to fit their audience. Embedded solutions often include APIs and customizable user flows, but also support and go-to-market components. As a result, platforms can launch new products and businesses, backed by the deep expertise of their embedded partners. The embedded fintech opportunity The embedded finance market is booming, currently valued at $185 billion and projected to reach $320 billion by 2030, with SMBs accounting for half of that growth. More than 60% of SMBs want embedded financial services that simplify payment processes; 50% of these businesses believe the solutions can provide valuable payment data and insights to improve their operations. Tech companies that successfully partner with others to offer SMBs tailored, embedded fintech options are tapping into a significant and often overlooked market. Over the past few years, weve partnered with dozens of tech companies like Xero, Lattice, and Collective, and financial institutions, like Chase Payment Solutions and U.S. Bank. Through the technology on our platform, Gusto Embedded, we help them offer payroll directly within their own platforms to their SMB customers. This gives SMBs the chance to access more of their operations on one platform, so they can handle their finances and run payroll all in the same place, using just one login. Five things to consider By helping partners build customizable payroll solutions, weve learned a lot about how to make embedded fintech solutions truly work for SMBs needs. For tech companies seeking to dive into embedded fintech to better serve SMBs, here are five key things to consider: Assess when to partner, and when to build it yourself: You should invest your R&D resources on your core differentiation and what makes you special in the eyes of your customers. Outside of this, consider testing demand with qualitative and quantitative user research as well as a referral partnership. When demand is sufficiently validated, focus on owning the user experience pieces that are unique to your platform, and outsource the rest to a partner. Another approach is a crawl-walk-run approach, where you start with a referral partnership and a light integration before graduating to an embedded or a white-label solution. Align leadership for success: If you decide to pursue an embedded partnership, ensure that your business and product leaders are on the same page with your partners leaders. Ensure everyone has bought into the product development process, the launch strategy, and customer support for the new product. This is vital for a successful rollout and for the best possible experience for your customers. Customization is key: Tailor embedded fintech experiences to be fit-for-purpose rather than relying on generic features. A recent example of this was our partnership with Vagaro. We worked closely with Vagaro to develop an embedded payroll solution catering to the complex wage structures of its customersprimarily salon, spa, and fitness businesses. Taking this approach cut the time spent on payroll processing in half and significantly increased user adoption. Take a thoughtful approach to rollout: Avoid the build it and they will come mentality. A lot of tech companies fall into the trap of building great software, while neglecting to create a strategic go-to-market approach. Ask potential partners how they can assist in promoting the solution to your mutual customers. Do they understand your customers’ needs? How can you work together to clearly communicate and educate customers on the new product? Build trust before launching: The pressure to quickly introduce new products can be intense, but its essential to innovate responsibly. Ensure the end-to-end experience is polished for your initial customers before expanding to a broader audience. In the fintech industry, trust is paramount, and a poor experience can jeopardize customer relationships. For SMBs, the path to growth in an increasingly complex and competitive landscape lies in embracing new technology, particularly through embedded fintech. It will be essential for tech companies to listen closely to the needs of small businesses and develop tailored products that address their most pressing concerns. Partnering with others can speed up that process and help meet SMBs needs faster. When your SMB clients succeed, you can unlock new growth opportunities, while helping SMBs thrive in a digital economy demanding constant agility and adaptability. Tomer London is cofounder and chief product officer at Gusto.
Category:
E-Commerce
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