Source: 1843 Magazine | April/May 2019
Author: Hal Hodson
One afternoon in August 2010, in a conference hall perched on the edge of San Francisco Bay, a 34-year-old Londoner called Demis Hassabis took to the stage. Walking to the podium with the deliberate gait of a man trying to control his nerves, he pursed his lips into a brief smile and began to speak: “So today I’m going to be talking about different approaches to building…” He stalled, as though just realising that he was stating his momentous ambition out loud. And then he said it: “AGI”.
AGI stands for artificial general intelligence, a hypothetical computer program that can perform intellectual tasks as well as, or better than, a human. AGI will be able to complete discrete tasks, such as recognising photos or translating languages, which are the single-minded focus of the multitude of artificial intelligences (AIs) that inhabit our phones and computers. But it will also add, subtract, play chess and speak French. It will also understand physics papers, compose novels, devise investment strategies and make delightful conversation with strangers. It will monitor nuclear reactions, manage electricity grids and traffic flow, and effortlessly succeed at everything else. AGI will make today’s most advanced AIs look like pocket calculators.
The only intelligence that can currently attempt all these tasks is the kind that humans are endowed with. But human intelligence is limited by the size of the skull that houses the brain. Its power is restricted by the puny amount of energy that the body is able to provide. Because AGI will run on computers, it will suffer none of these constraints. Its intelligence will be limited only by the number of processors available. AGI may start by monitoring nuclear reactions. But soon enough it will discover new sources of energy by digesting more physics papers in a second than a human could in a thousand lifetimes. Human-level intelligence, coupled with the speed and scalability of computers, will make problems that currently appear insoluble disappear. Hassabis told the Observer, a British newspaper, that he expected AGI to master, among other disciplines, “cancer, climate change, energy, genomics, macro-economics [and] financial systems”.
The conference at which Hassabis spoke was called the Singularity Summit. “The Singularity” refers to the most likely consequence of the advent of AGI, according to futurists. Because AGI will process information at high speed, it will become very smart very quickly. Rapid cycles of self-improvement will lead to an explosion of machine intelligence, leaving humans choking on silicon dust. Since this future is constructed entirely on a scaffolding of untested presumptions, it is a matter of almost religious belief whether one considers the Singularity to be Utopia or hell.
Judging by the titles of talks, the attendees at the conference tended towards the messianic: “The Mind and How to Build One”; “AI against Aging”; “Replacing Our Bodies”; “Modifying the Boundary between Life and Death”. Hassabis’s speech, by contrast, appeared underwhelming: “A Systems Neuroscience Approach to Building AGI”.
Hassabis paced between the podium and a screen, speaking at a rapid clip. He wore a maroon jumper and a white button-down shirt like a schoolboy. His slight stature seemed only to magnify his intellect. Up until now, Hassabis explained, scientists had approached AGI from two directions. On one track, known as symbolic AI, human researchers tried to describe and program all the rules needed for a system that could think like a human. This approach was popular in the 1980s and 1990s, but hadn’t produced the desired results. Hassabis believed that the brain’s mental architecture was too subtle to be described in this way.
The other track comprised researchers trying to replicate the brain’s physical networks in digital form. This made a certain kind of sense. After all, the brain is the seat of human intelligence. But those researchers were also misguided, said Hassabis. Their task was on the same scale as mapping every star in the universe. More fundamentally, it focused on the wrong level of brain function. It was like trying to understand how Microsoft Excel works by tearing open a computer and examining the interactions of the transistors.
Instead, Hassabis proposed a middle ground: AGI should take inspiration from the broad methods by which the brain processes information – not the physical systems or the particular rules it applies in specific situations. In other words it should focus on understanding the brain’s software, not its hardware. New techniques like functional magnetic resonance imaging (fMRI), which made it possible to peer inside the brain while it engaged in activities, had started to make this kind of understanding feasible. The latest studies, he told the audience, showed that the brain learns by replaying experiences during sleep, in order to derive general principles. AI researchers should emulate this kind of system.
A logo appeared in the lower-right corner of his opening slide, a circular swirl of blue. Two words, closed up, were printed underneath it: DeepMind. This was the first time the company had been referred to in public. Hassabis had spent a year trying to get an invitation to the Singularity Summit. The lecture was an alibi. What he really needed was one minute with Peter Thiel, the Silicon Valley billionaire who funded the conference. Hassabis wanted Thiel’s investment.