Quantum ( 量子 ) computers have been on my mind a lot lately. A friend has been sending me articles on how quantum computers might help solve some of the biggest challenges we face as humans. I’ve also had exchanges with two quantum-computing experts. One is computer scientist Chris Johnson who I see as someone who helps keep the field honest. The other is physicist Philip Taylor.

For decades, quantum computing has been little more than a laboratory curiosity. Now, big tech companies have invested in quantum computing, as have many smaller ones. According to Business Weekly, quantum machines could help us “cure cancer, and even take steps to turn climate change in the opposite direction.” This is the sort of hype ( 炒作 ) that annoys Johnson. He worries that researchers are making promises they can’t keep. “What’s new,” Johnson wrote, “is that millions of dollars are now potentially available to quantum computing researchers.”

As quantum computing attracts more attention and funding, researchers may mislead investors, journalists, the public and, worst of all, themselves about their work’s potential. If researchers can’t keep their promises, excitement might give way to doubt, disappointment and anger, Johnson warns. Lots of other technologies have gone through stages of excitement. But something about quantum computing makes it especially prone to hype, Johnson suggests, perhaps because “‘quantum’ stands for something cool you shouldn’t be able to understand.” And that brings me back to Taylor, who suggested that I read his book Q for Quantum.

After I read the book, Taylor patiently answered my questions about it. He also answered my questions about PyQuantum, the firm he co-founded in 2016. Taylor shares Johnson’s concerns about hype, but he says those concerns do not apply to PyQuantum.

The company, he says, is closer than any other firm “by a very large margin ( 幅度 )” to building a “useful” quantum computer, one that “solves an impactful problem that we would not have been able to solve otherwise.” He adds, “People will naturally discount my opinions, but I have spent a lot of time quantitatively comparing what we are doing with others.”

Could PyQuantum really be leading all the competition “by a wide margin”, as Taylor claims? I don’t know. I’m certainly not going to advise my friend or anyone else to invest in quantum computers. But I trust Taylor, just as I trust Johnson.

What is life? Like most great questions, this one is easy to ask but difficult to answer. The reason is simple: we know of just one type of life and it’s challenging to do science with a sample size of one. The field of artificial life-called ALife for short — is the systematic attempt to spell out life’s fundamental principles. Many of these practitioners, so-called ALifers, think that somehow making life is the surest way to really understand what life is.

So far no one has convincingly made artificial life. This track record makes ALife a ripe target for criticism, such as declarations of the field’s doubtful scientific value. Alan Smith, a complexity scientist, is tired of such complaints. Asking about “the point” of ALife might be, well, missing the point entirely, he says. “The existence of a living system is not about the use of anything.” Alan says. “Some people ask me, ‘So what’s the worth of artificial life?’ Do you ever think, ‘What is the worth of your grandmother?’”

As much as many ALifers hate emphasizing their research’s applications, the attempts to create artificial life could have practical payoffs. Artificial intelligence may be considered ALife’s cousin in that researchers in both fields are enamored by a concept called open-ended evolution (演化). This is the capacity for a system to create essentially endless complexity, to be a sort of “novelty generator”. The only system known to exhibit this is Earth’s biosphere. If the field of ALife manages to reproduce life’s endless “creativity” in some virtual model, those same principles could give rise to truly inventive machines.

Compared with the developments of Al, advances in ALife are harder to recognize. One reason is that ALife is a field in which the central concept — life itself — is undefined. The lack of agreement among ALifers doesn’t help either. The result is a diverse line of projects that each advance along their unique paths. For better or worse, ALife mirrors the very subject it studies. Its muddled (混乱的) progression is a striking parallel (平行线) to the evolutionary struggles that have shaped Earth biosphere.

Undefined and uncontrolled, ALife drives its followers to repurpose old ideas and generated novelty. It may be, of course, that these characteristics aren’t in any way surprising or singular. They may apply universally to all acts of evolution. Ultimately ALife may be nothing special. But even this dismissal suggests something：perhaps, just like life itself throughout the universe, the rise of ALife will prove unavoidable.