Zomato's founder says he discovered a number that measures the cost of being alive. The engineering underneath is genuinely clever. The word "discovered" is doing a lot of heavy lifting here it seems.
Deepinder Goyal posted something this week that did exactly what it was built to do. It made you stop scrolling.
The man who turned India’s food delivery into a verb has a new company called Temple, and Temple, he says, has “discovered (literally discovered) a biomarker, only readable on the temple region, and nowhere else, that measures the real-time cost of you being alive.” They’re calling it Entropy. A live number, 1 to 250, ticking every second on your wrist’s spiritual cousin: a sensor that clips onto the side of your head.
I read that post three times. The first time as a person, and I’ll admit it gave me that little hit of sci-fi wonder. The second time as someone who’s spent two decades around measurement systems, where the word “discovered” tends to trigger a small, involuntary flinch. And the third time trying to hold both reactions at once, because the honest truth about Temple is that it’s neither the miracle the post implies nor the snake oil your cynical friend will call it in the group chat.
It’s something more interesting than either. So let me actually take it apart.
What Temple is actually measuring
Start with the part that’s real, because it’s genuinely smart.
Temple isn’t magic. Underneath the marketing, the device uses two well-established optical techniques: near-infrared spectroscopy and reflective photoplethysmography. In plain terms, it shines light into the tissue at your temple and reads how blood is moving and how oxygenated it is. It’s tracking cerebral blood flow, the supply line to your brain, continuously, in real time.
And here’s the actually-clever insight, the one I tip my hat to. Why the temple, specifically? Because your skull doesn’t bounce. Every wrist wearable on earth fights a losing war against motion: your arm swings, the watch slides, the signal turns to noise, and the device guesses to fill the gaps. The side of your head is one of the most mechanically stable pieces of real estate on your body. Bolt a sensor there and the motion artifacts that wreck wrist data largely vanish. You get a clean, high-resolution pulse wave you can actually do math on.
That’s not nothing. That’s a real engineering decision with a real rationale.
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So far, so good. A clever sensor in a clever spot, reading a real physiological signal. The eyebrow goes up at the next word.
The word “discovered” is carrying a nation on its back
Goyal says Temple “discovered” a biomarker. I want to be careful here, because this is where excitement and accuracy quietly part ways.
Entropy, as a concept applied to brain and body signals, is not new. There’s a whole research literature on “brain entropy,” the mathematical complexity of physiological signals, going back years. Scientists have linked signal entropy to cerebral blood flow, to caffeine, to anaesthesia depth, to meditation, to a dozen conditions. Temple’s own scientific framing leans on exactly this body of work. The math that turns a messy pulse wave into a “complexity” number is established territory.
So what did Temple actually do? Most likely, and this is genuinely useful if true, they built a consumer device that computes a version of this signal continuously, cleanly, from a clever location, and packaged it into a single legible number you’ll actually look at. That’s productization, and good productization changes lives. The iPhone didn’t discover the touchscreen either.
But “we built a slick continuous monitor for an existing class of signal” doesn’t trend. “We literally discovered the cost of being alive” does. The gap between those two sentences is the gap between engineering and marketing, and you should always know which one you’re reading.
A biomarker isn’t something you announce. It’s something that survives other people trying to break it.
That’s the part missing so far. Not a study. Not a name. Survival.
About that beautiful 0.93
Here’s the number doing the persuading. Temple says that over a hundred cardio sessions, Entropy tracked a lab-grade metabolic cart at a correlation of 0.93, while plain heart rate managed a limp 0.55. The implication lands instantly: Entropy is nearly twice as good at reading your body’s true energy cost.
Take it seriously, because it might be real. A 0.93 correlation against indirect calorimetry, the actual gold standard for energy expenditure, would be a strong result for a wearable. If it holds, it’s a legitimately good number.
Now hold it at arm’s length, because three things are unsaid, and in measurement the unsaid is where the bodies are buried.
First, it’s one source. These numbers come from the company selling the device, in a marketing post, with no independent replication and no peer review. That’s not an accusation of dishonesty. It’s just the difference between “we measured this” and “this has been verified.” Every wearable startup’s internal numbers look great. That’s survivorship, not validation.
Second, “cardio sessions” is a narrow, friendly test. During steady exercise, almost everything in your body, heart rate included, correlates with everything else, because they’re all being driven up the same ramp by the same effort. The hard question isn’t whether Entropy tracks calorimetry while you’re cycling. It’s whether it says anything trustworthy during the messy 23 hours a day you’re not. A meal, a stressful email, a bad night, a cold plunge. That’s where the claim has to earn its keep, and we haven’t seen that data.
Third, heart rate at 0.55 is a slightly soft opponent. Energy expenditure has never been heart rate’s job. Beating it at a task it was never designed for is a real but modest flex.
None of this means the number is fake. It means the number is a beginning, not a verdict. The right posture toward a single impressive self-reported correlation is curiosity with a seatbelt on.
The Maxima and Minima idea is the part I actually like
Strip away the breathless framing and there’s a genuinely elegant concept hiding in Goyal’s post.
He describes two derived numbers. Your Entropy Maxima is the ceiling, the highest cost your body can hit when you push hard, which he frames as a marker of capacity that naturally falls with age. Your Entropy Minima is the floor, the lowest your body settles to at rest, which he ties to the old, well-supported observation that across species, a lower resting metabolic cost tends to travel with a longer life.
I like this because it reframes a single number into a range, and range is where the real physiological story lives. A healthy body isn’t one that sits at a magic value. It’s one that can surge high when challenged and sink low when it rests, and move between the two quickly. Push the ceiling up, pull the floor down, recover fast in between. As a mental model for fitness, that’s better than most of what your smartwatch tells you, and it’s intuitive enough to actually change behavior.
The science underneath is real-ish and partly speculative, the cross-species longevity link is suggestive, not a law you can bank your healthspan on. But as a frame for paying attention to your own body, it’s legitimately good. Sometimes the value of a metric isn’t its precision. It’s that it makes you notice.
So should you care about Temple?
Here’s where I land, holding both reactions at once.
The hardware idea is smart. The location insight is real. The optical methods are sound. The Maxima/Minima framing is a genuinely nice way to think about fitness. And the productization, turning a research-grade signal into a number you’ll glance at every day, is exactly the kind of unglamorous work that occasionally does change how millions of people relate to their bodies.
But the language is running about ten lengths ahead of the evidence. “Discovered a biomarker” should be “built a continuous monitor for one.” “Measures the cost of being alive” should be “estimates metabolic demand from cerebral blood flow, pending independent validation.” And the single most important number in the whole pitch, that 0.93, is currently a promise wearing the costume of a proof.
The good news is that this is all knowable. A biomarker earns its name in public, when independent labs run it, when it’s tested on the boring 23 hours and not just the flattering hour, when someone who doesn’t profit from the answer tries hard to break it and fails. Temple says it won’t ship “before it’s perfect.” Fine. The thing to watch isn’t the launch. It’s whether the peer-reviewed paper ever shows up behind the trademark symbol.
Because here’s the quiet tell, the one I keep coming back to. A real breakthrough biomarker doesn’t usually arrive trademarked, on a home screen, with a marketing name, before it arrives in a journal.
Sometimes that order gets reversed and the science still turns out to be sound. It happens. But when the beautiful number shows up first and the verification is promised for later, the most useful thing you can do is exactly what Temple says its device does.
Watch the live signal closely. And don’t fully trust it yet.
I’ve spent about two decades building data and AI systems, the kind where someone shows you a gorgeous correlation and your first job is to find out what it’s hiding. I write about the space where technology, hype, and what’s actually true keep getting tangled, and how to tell them apart. If this helped you read one breakthrough headline more clearly, subscribe. There’s always another beautiful number coming.
Sources / further reading: Deepinder Goyal’s public post announcing Temple’s “Entropy” biomarker (June 2026). BusinessToday and Storyboard18 coverage of the announcement and the metabolic-cart benchmarking claims (2026). TechCrunch on Temple’s $54M raise and cerebral-blood-flow premise (Feb 2026). On the underlying science of signal/brain entropy and cerebral blood flow: Wang et al., “Associations of brain entropy to cerebral blood flow” (PubMed, 2019); “Caffeine Caused a Widespread Increase of Resting Brain Entropy,” Scientific Reports (2018); EEG spectral entropy and regional cerebral blood flow studies. Note: Temple’s specific Entropy metric had not been independently peer-reviewed at the time of writing.