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The merge

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I first heard of the merge from Sam Altman’s blog. He said that it was a popular topic of conversation in Silicon Valley to guess when (not if) humans and machines will merge. In a meaningful way rather than just a Johnny Mnemonic-style walking data storage unit.

When I heard of this definition of the merge, I immediately thought of the digital series H+.

H+ The Digital Series

H+ told the tale of a technological hack that killed people by disrupting the implants in their heads. Some of the few survivors were out of cellular network reach in the basement of multi-story car park.

He went on to explain that it may not be a hybridisation of humans literally with technology but when humans are surpassed by a rapidly improving (general purpose) AI. The third possibility was a genetically enhanced species surpassing humans in the same way that homo sapiens surpassed the neanderthal.

What’s interesting is that some of the people don’t give ‘the merge’ a name at all. Back during the dot com boom, when Ray Kurzweil published his book Age of Spiritual Machines it was given the name The Singularity.

Part of the resistance to this established term was that The Singularity implies a single point in time. I don’t think Kurzweil meant it in that way. But its been almost 20 years since I read Age of Spiritual Machines, and I suspect most of the debaters have only read about it from a Wikipedia article.

Alton points out that in some ways the merge has been with us for a good while.

The contacts app on our devices and social networks take the place of us remembering telephone numbers. I can remember my parents landline number and the number of the first family doctor that we had. But I wouldn’t be able to tell you my parents current cell phone number; or the number of my current doctor.

On a grander scale; general knowledge and desire to read around has been depreciated by Google and Wikipedia. Our phones, tablets and laptops are not implanted in us, but at least one of them will be seldom out of reach. I learned to touch type and I am now not conscious of how I input the text into this post. It goes from my thought to the screen. Only the noise of the keys gives away illusion of mind control as I stare at the screen. Ironically voice assistance makes me more conscious of ‘the other’ nature of the device.

But it no longer just about memory and our personal connectedness of the devices. Our device control us and suggest what to do and when. Social media platform curation affects how we feel.

As Altman puts it:

We are already in the phase of co-evolution — the AIs affect, effect, and infect us, and then we improve the AI. We build more computing power and run the AI on it, and it figures out how to build even better chips.

This probably cannot be stopped. As we have learned, scientific advancement eventually happens if the laws of physics do not prevent it.

Sam Altman – The Merge

Innovation often spits out the same process in several waves before it works. Before Siri, Alexa and Google home there was Wildfire. Before Wildfire there were various speech recognition technologies including Nuance for call centres, Lernout & Hauspie, Dragon Systems and Kurzweil Computer Systems. The last two were founded in the mid-1970s. SRI International’s AI research started delivering results in the mid 1960s.

AI in its broadest terms has gone through several research booms and busts. The busts have their own name ‘AI winters’. The cadence of progress could easily be far slower than Altman imagines.

One could easily argue that machine learning might run its natural course to technical maturity without much more improvement. Google and other technology companies are basing their work on research done at Canadian universities in the 1980s during an ‘AI winter’ characterised by a lack of basic research funding. Canada continued to support the research when others didn’t.

Silicon Valley companies not engaging in basic research themselves. As Judy Estrin observed in her book Closing The Innovation Gap back in 2008, Silicon Valley no longer engages in ‘hard innovation’. Without that basic research; a general purpose AI envisioned by Kurzweil and Altman maybe out of reach. Which is why Silicon Valley pundits put the merge as somewhere in a 50-year window.

Altman also caveats his prediction based on the laws of physics. Aaron Toponce : The Physics of Brute Force provides an idea of the physical limits imposed by cracking cryptography. It would not be inconceivable that a general purpose AI may hit similar challenges. More on machine learning and innovation here.