All of this seems to point to a glum future where unfettered and dangerous AI proliferates. But the companies beg to differ. When I presented my bleak argument, they insisted that safety was as important as ever, despite the Pentagon’s affection for unreliable killer drones. “I don't think the race to the top is dead,” says Anthropic’s chief science officer Jared Kaplan, urging me to shift my gaze from the battlefield and the marketplace to the research labs. “There are a lot of researchers at every lab that care a lot about doing the right thing. They want to see their research used for the betterment of humanity, and I think there is competition not just to make them more useful or capable, but also safer,” he tells me.
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Nanopore sequencing, thought of in the eighties, further developed along the years51 and first commercialized by ONT in 201452, is completely different from all the sequencing technologies previously mentioned. Where all the other ones are based on synthesizing a complementary DNA strand and detecting specific dNTP incorporation in some way or another, there is no synthesis in nanopore sequencing. The principle relies on feeding a single strand of a DNA template through a small hole in a membrane, a nanopore, at a controlled speed. As the nucleotides go through the nanopore, an electric current is formed between both sides of the membrane. This current can be measured and is specific to the succession of 5 to 6 nucleotides inside the nanopore channel at any given time. By looking at the evolution of the electric current as the DNA strand goes through the nanopore, we can deduce the sequence of nucleotides through a process called base calling. Base calling is usually done with machine learning methods, mainly artificial neural networks53. In the flow cells used in ONT sequencers, there are hundreds of thousands of nanopores, spread out over a synthetic membrane, allowing for massively parallel sequencing as well. Theoretically, since this method is not based on synthesis, the upper limit for read length is only limited by the length of the template, and in practice ONT sequencing produces the longest reads.
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