Archaeology meets big tech, the cognitive cost of AI, heat-proofing plants, and energy-saving computer chips

📜 A 12,000-year-old story

A recent archaeological discovery suggests a major cultural milestone: the onset of naturalistic depictions of people with animals around 12,000 years ago, almost three thousand years earlier than previously estimated. Science News’s Bruce Bower has more on this ancient narrative shift.

🖌️ The original content creators

For millennia, Paleolithic art was dominated by animals. Think cave paintings of bison, carvings of horses and not many humans among them. A new finding, unearthed in modern-day Israel, marks a departure.Archaeologists studying an ancient figurine, timeworn and abstract to the naked eye, used “technological, archaeometric and dermatoglyphic analyses” to reconstruct a figure of a woman and a goose in a relationship of intimacy, or perhaps domestication.

Say what? Let’s parse these techniques one by one: 👇

Technological analysis refers to the scientific study of how an object was made, in order to reconstruct the sequence of actions, the knowledge and the tools used by ancient artisans. This could include microscopy (using high-powered optical or scanning electron microscopes), or radiography (using X-rays or CT scans), to see inside complex objects. 

Archaeometry is the application of the physical and chemical sciences to determine composition, date and provenance of artifacts and environmental remains. 

Dermatoglyphic analysis refers to identifying dermal ridges (fingerprints, palm prints and foot prints) to detect ancient prints left on soft materials.

The upshot: Scientists believe the discovery signals a profound psychological shift in human behavior, when myths and stories pivoted from nature worship to a time when humans began to place themselves in a spiritual narrative.

🗿Digitizing the dust: The business of computational archaeology

The contemporary field of archaeology is evolving to include industrial-grade 3-D scanning and photogrammetry (stitching 2-D images into hyper-realistic 3-D models. AI-driven pattern recognition can also analyze these 3-D datasets to classify fragments, identify toolmarks invisible to the naked eye and perform a sort of virtual restoration. This technology is creating a new asset class: digital heritage. Technology companies are getting in on educational licensing deals, consulting for immersive museum experiences and helping to create proprietary digital archives for augmented reality and spatial computing applications.

💽 Financing the digital replica

Archaeology is finding a convergence between heritage preservation and next-gen augmented reality infrastructure. Here are a few companies at the forefront of this field:

• CyArk, a pioneer in the digital preservation space, uses laser scanning to create precise 3-D blueprints of world heritage sites. While not a traditional VC target, they have secured over $400,000 in grants, with support from corporate partners like Google, Iron Mountain and Seagate, validating the commercial demand for high-fidelity reality capture data.
  
• Scaniverse, founded in 2020 and acquired in 2021 by augmented reality giant Niantic (creators of the viral game Pokémon GO), makes high-fidelity 3-D scanning technology that works with cell phones. It transforms physical objects into digital twins for applications like archaeology. In 2025, Niantic sold its games business and spun out a new startup, Niantic Spatial, with $250 million in funding. They are currently leveraging Scaniverse’s technology not just for scanning smaller locations such as statues, but to crowdsource a “Visual Positioning System” (VPS)—essentially a detailed 3-D map that allows augmented reality content (and potentially historical overlays) anywhere in the world, including places where GPS is denied or compromised.

The future of the spatial economy is quite literally being built on the dust of the past.

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☹️ Is AI making us dumber?

Never underestimate the human capacity for shortcuts. Ask any student today, and they’re likely to tell you they’re using AI to help them meet looming academic deadlines and streamline school workloads. But lo and behold, in the long run, these timesavers are setting us back. New research from experts at the University of Pennsylvania suggests that the superficial nature of LLMs may be hurting people who rely upon it to learn something new. Payal Dhar reports for SN on the shortcomings of AI in learning.

🤷‍♀️ The cognitive cost of convenience

A research team from the University of Pennsylvania conducted a series of experiments involving over 10,000 participants to compare learning outcomes when researching new topics (like gardening or healthy living) using either a traditional web search engine (Google) or an AI chatbot (ChatGPT). The participants were then asked to write about their newfound knowledge to teach it to someone else. They found that participants who analyzed results from their own web searches developed “deeper knowledge,” as measured by natural language processing and human judges, and were more invested in the advice they gave. The researchers concluded that the ease of receiving synthesized information from LLMs came at the cost of developing genuine understanding.

🎓 Education means proving evidence of understanding

In response to students using chatbots to generate plausible-but-shallow assignments, educators are moving away from grading the final product (which AI can fake) and toward evaluating the process and the evidence of thinking (which AI cannot easily replicate). That means annotated drafts, detailed research logs showing query evolution, in-class discussions and unique, highly contextualized assignments that an LLM cannot generalize from the public web. Furthermore, educators are prioritizing tasks that require synthesis across disparate modalities — for example, analyzing a specific local dataset or responding to a real-time, non-digital event — forcing students to demonstrate original, human-driven critical thinking rather than just output generation.

✅ The verification economy: investing in the ‘how’

Enter EdTech. Since the rise of AI in education, new tools have emerged and existing tech has evolved to serve researchers looking to increase their ability to verify authenticity, and educators seeking to scaffold deeper reasoning. Interestingly, some of these tools also use AI. Here are a few worth learning about:

• Elicit: This platform focuses on automating scientific workflows by answering research questions using high-quality academic papers and summarizing key takeaways. While Elicit’s product uses AI, its focus on providing robust citations and filtering out retracted papers makes it a critical tool for verifying information integrity. Elicit secured a $9 million seed round in 2023 to scale its research-focused AI.
  
• Turnitin: While an established player in spotting plagiarism, Turnitin is rapidly expanding its core “verification suite” to include AI writing detection. The investment focus here is on integrated assessment tools in the platform that help educators redesign assignments to be “AI-resistant” while maintaining academic integrity. Turnitin was acquired by Advance Publications for $1.75 billion in 2019.
  
• Harmonic offers an AI-driven mathematical engine with applications in theorem proving, software verification and education. Trained with reinforcement learning, a trial-and-error process where an AI gets virtual rewards for doing something right, Harmonic’s platform is designed with the aim of having an interpretable step-by-step process that could be used in safety-critical systems in fields where software failure can be catastrophic, such as aerospace (flight control systems), automotive (self-driving car algorithms), and medical devices. They’ve raised $295 million to date, including a $120 million series C round last month with investment by Sequoia Partners and Kleiner Perkins.

Harnessing AI to cultivate authentic critical thinking? We’re here for it.

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🏜 Hothouse flowers: Engineering heat-resilient plants

A flowering desert shrub that thrives in blistering heat stumped researchers for decades — until a recent discovery at the cellular level revealed a striking adaptation. Siddhant Pusdekar reports for SN on how the Arizona honeysweet’s shapeshifting insides helps it flourish in extreme climates.

🎋 Photosynthetic acclimation

The Arizona honeysweet (Tidestromia oblongifolia) grows best in blistering heat. In 1972, researchers demonstrated that this plant’s ability to perform photosynthesis — the vital process of converting sunlight into energy — peaks at over 116° Fahrenheit (47° Celsius), marking the highest known peak-performance temperature for any plant. But they didn’t know why this was the case.

In a paper published this past November in the journal Current Biology, another team of researchers investigated T. oblongifolia’s photosynthesis rates in the lab. They kept plants for eight weeks at nearly 89° F (31° C) before turning the heat up for some to over 116° F (47° C). Plants in the hotter setting tripled in size over another eight days. The researchers call this adaptation “photosynthetic acclimation.”

But the team didn’t stop there — they looked under the microscope at the shrubs’ chloroplasts, or the cell organelles that perform photosynthesis. While most plants’ chloroplasts sustain damage in such heat, T. oblongifolia’s remained intact. But also, the chloroplasts in specialized leaf cells that convert carbon dioxide to sugar had taken on a novel, cup shape. Arizona honeysweet displayed other adaptations, too, like growing smaller leaves with smaller cells, activating damage repair genes and rehabilitating a photosynthesis enzyme.

🧬 Heat-proofing plants

This paper also reveals that heat-proofing a plant isn’t as simple as adjusting a gene here and a protein there. Still, understanding how T. oblongifolia acclimates could serve as inspiration for heat-proofing other plants as temperatures rise around the world. Most greens aren’t like the Arizona honeysweet; they perform heat-limited photosynthesis, and in temperatures higher than what they’re used to, they may not grow as well, or even suffer on the cellular level. Investing in technology that can help plants all over the planet adapt now can mean preserving more species — including those that may be key to our diet or pollination — as longer, hotter seasons become the norm.

🌱 Planting ideas

Here are a few companies whose technology seeks to make plants more climate-resilient, if not bequeath them photosynthetic acclimation:

• Plantik Biosciences: This Paris-based, seed-stage company develops technology that enables plants’ resilience during heatwaves. Founded in 2019, they’ve raised $100,000 so far.
  
• Inari: This Cambridge, Massachusetts–based Series G company is designing seeds that need less water and fertilizer and have higher crop yields. By building a trove of plant gene data and honing the ability to edit multiple genes with multiple techniques at once, they aim to produce more resilient strains. This past January they raised $144 million, bringing their total funding to $753 million.
  
• Tropic Biosciences: Founded in 2016, this London-based Series C startup uses gene editing tech to create disease- and climate-resilient tropical crops by promoting or suppressing certain genes in coffee, bananas and rice. Over four funding rounds they’ve raised over $73 million, counting Temasek Holdings and Aliment Capital among their lead investors.

This science may help seed the future of more heat-resilient plants.

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🧊 Ice River: A computer chip that reuses energy

You’ve probably felt your laptop heat up before. All that warmth comes from wasted energy as the computer performs function after function. But an experimental computer chip can reuse the electrical energy running through it. Kathryn Hulick reports for SN on Ice River, a new chip that can recover some of its wasted energy.

🔨 Un-computing with reversible logic

Traditional chips waste energy in a few ways. Their circuitry only processes information in one direction, with every new computation erasing previous ones, generating heat. They also fritter away electricity through rapid voltage changes. Like a hammer slamming down, the coursing electricity smashes 1s into 0s or the other way around, a rapid change that creates speedy computations but also heat.

Ice River modifies these two wasteful phenomena. Rather than process information in only one direction, it employs what’s called reversible logic, allowing it to un-compute and recover original information, which avoids wasting heat on erasures. And instead of smashing 1s into 0s, it uses an approach called adiabatic computing, where voltages fluctuate gradually — it acts like a pendulum instead of a hammer.

Tested in August by its makers at startup Vaire Computing, this chip used around 30 percent less energy compared to a traditional chip performing the same computations, reusing some of its electrical energy.

💻 Unprecedented technology for unprecedented progress

As artificial intelligence continues to ratchet up, more efficient computer chips are on everyone’s wish lists. Data centers already require massive amounts of water and constant cooling in order to keep computers from overheating, and AI demands powerful computer chips that perform on even more electricity. While Ice River is only experimental technology, it may serve as one blueprint for the future of cooler, more energy-efficient computer chips.

⚡ Low power, high tech

Though Ice River seems to be the only product of its kind in public right now, other startups have energy-efficient computing on the brain.

• Vaire Computing: The creator of Ice River is based in London. Their more energy-efficient hardware is geared toward a cooler future of computing. Since their founding in 2021, they’ve raised $10 million.
  
• Ambiq: Founded in 2010, this Austin, Texas–based startup produces energy-efficient systems on a chip — an integrated circuit that combines myriad functions, like processing and storing memory, into a single chip — destined for “ultra-low power” products such as smartwatches and gaming devices. They’ve raised a total of $387.1 million.
  
• NeoLogic: This Series A startup based in Israel develops more efficient computer processors. Their technology reportedly saves up to 40 percent of the area a processor usually takes up, and dissipates up to 50 percent less power. Founded in 2021, they most recently raised $10 million this past August, bringing their total funding to $18 million.

These chips are looking pretty cool.

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