PIONEERWORKS – BROADCAST
Longevity technologies are inspiring a new philosophy around aging and mortality.
Category Archives: Feature
Machines Learn Better if We Teach Them the Basics
QUANTA MAGAZINE
A wave of research improves reinforcement learning algorithms by pre-training them as if they were human.
Imagine that your neighbor calls to ask a favor: Could you please feed their pet rabbit some carrot slices? Easy enough, you’d think. You can imagine their kitchen, even if you’ve never been there — carrots in a fridge, a drawer holding various knives. It’s abstract knowledge: You don’t know what your neighbor’s carrots and knives look like exactly, but you won’t take a spoon to a cucumber.
Artificial intelligence programs can’t compete. What seems to you like an easy task is a huge undertaking for current algorithms.
A Real-Life Body Clock
GROW
A blood test says you’re aging too fast. Now what?
HOLLY MANN remembers a time — it must have been twelve years ago — when she started feeling old. Then 27, the US Army veteran found that she could no longer comfortably exercise. She was sapped of energy, and carried pain in her shoulders, hip, knees, and wrists. “I had a lot of issues that I would frankly associate with somebody who was two decades older than me,” she says. The doctors said that her symptoms stemmed from months of undetected carbon monoxide poisoning. They couldn’t tell her any more than that. Ms. Mann was desperate to feel better — really, she says, to feel younger.
Consulting the internet, she started tinkering with her diet. She tried new workouts. She ordered capsules of Vitamin This and Supplement That. And a few years in, after incremental ups and downs, she started to see real improvements. Though she still faced her share of low-energy days, by 2020, Mann felt noticeably better. She was curious: how much better? Had she, possibly, turned back the hands of time?
Machine Learning Gets a Quantum Speedup
QUANTA MAGAZINE
Two teams have shown how quantum approaches can solve problems faster than classical computers, bringing physics and computer science closer together.
For Valeria Saggio to boot up the computer in her former Vienna lab, she needed a special crystal, only as big as her fingernail. Saggio would place it gently into a small copper box, a tiny electric oven, which would heat the crystal to 77 degrees Fahrenheit. Then she would switch on a laser to bombard the crystal with a beam of photons.
This crystal, at this precise temperature, would split some of those photons into two photons. One of these would go straight to a light detector, its journey finished; the other would travel into a tiny silicon chip — a quantum computing processor. Miniature instruments on the chip could drive the photon down different paths, but ultimately there were only two outcomes: the right way, and the many wrong ways. Based on the result, her processor could choose another path and try again.
The sequence feels more Rube Goldberg than Windows, but the goal was to have a quantum computer teach itself a task: Find the right way out.
Surprising Limits Discovered in Quest for Optimal Solutions
Quanta Magazine
Algorithms that zero in on solutions to optimization problems are the beating heart of machine reasoning. New results reveal surprising limits.
Our lives are a succession of optimization problems. They occur when we search for the fastest route home from work or attempt to balance cost and quality on a trip to the store, or even when we decide how to spend limited free time before bed.
These scenarios and many others can be represented as a mathematical optimization problem. Making the best decisions is a matter of finding their optimal solutions. And for a world steeped in optimization, two recent results provide both good and bad news.
In a paper posted in August 2020, Amir Ali Ahmadi of Princeton University and his former student, Jeffrey Zhang, who is now at Carnegie Mellon University, established that for some quadratic optimization problems — in which pairs of variables can interact — it’s computationally infeasible to find even locally optimal solutions in a time-efficient manner.
But then, two days later, Zhang and Ahmadi released a second paper with a positive takeaway. They proved that it’s always possible to quickly identify whether a cubic polynomial — which can feature three-way interactions between variables — has a local minimum, and to find it if it does.
The limits are not what their discoverers expected.
The Race to Put Silk in Nearly Everything
WIRED
The fiber has been considered a “miracle material” for anything from body parts to food. Has the revolution finally arrived?
ALI ALWATTARI STILL remembers the day he met the goats. It was mid-May, 19 years ago, in Quebec. The sun was lighting up the old maple sugar farm—and small huts where the goats were living. Alwattari, a materials scientist, had spent his career tinkering with chemistry equipment for Procter & Gamble, developing fibers used in Pampers and Swiffers. But the startup Nexia Biotechnologies was aiming to use an entirely different kind of polymer producer—and it was gazing back at him with its rectangular pupils.
The Long, Strange Life of the World’s Oldest Naked Mole Rat
WIRED
These death-defying rodents do not age normally. Will their weird biology help extend human life spans, or are those ambitions a dead end?
JOE HAS LOOKED old since the day he was born, back in 1982. He’s pink and squinty and wrinkly. His teeth are weird: His incisors sit outside his lips to keep the dirt out of his mouth as he digs tunnels for his tube-shaped body.
“He looks remarkably the same,” says Rochelle Buffenstein, a comparative biologist who has studied naked mole rats since the 1980s when she was doing her doctoral work in Cape Town, South Africa. That’s where she met Joe. (He doesn’t have an official name, so we’re going with Joe.) A few years later, Buffenstein was starting her own research on vitamin D metabolism in mole rats because they spend all their time in dark tunnels, away from the sun. She moved to Johannesburg with a few subjects to begin her work, leaving Joe behind. He was eventually shipped off to the Cincinnati Zoo. But he and Buffenstein would soon reunite.
Max G. Levy 