Unprecedented Accuracy.

Still counting in California.

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1. Scientists at Columbia University have edited the DNA of early human embryos with unprecedented accuracy, an achievement that could open the way to babies engineered with particular characteristics. The prospect has fueled controversy for years. On the one hand, the technology might one day enable parents to safely repair disease-causing mutations in embryos. But it might also be used to select desired traits — a practice that some ethicists have argued is nothing short of eugenics. Dieter Egli, a geneticist at Columbia University who led the research, called for a public conversation about the pros and cons of altering embryonic DNA. “As a scientist, you can provide the data for discussion, but then essentially there you stop and let others take over,” he said. With a newer technology called base editing, Dr. Egli and his colleagues were able to meticulously replace individual genetic letters in sequences of DNA without causing the damage often observed with an earlier form of gene editing, CRISPR. Dr. Egli cautioned that the research left unanswered many questions about harmful side effects. “We’re not saying this is going to be used tomorrow in the clinics,” he said. Dr. Egli and his colleagues posted their study online. The research is under review for publication in a scientific journal. (Source: nytimes.com, biorxiv.org)

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2. The story of GLP-1 drugs keeps getting bigger. First they transformed the treatment of diabetes. Then they upended the science — and culture — of weight loss. Now a growing body of research is raising another possibility: that these drugs may help protect against cancer. At this year’s American Society of Clinical Oncology (ASCO) meeting in Chicago, more than 40 studies, abstracts, oral presentations and poster presentations examined the relationship between GLP-1-based drugs and cancer. The results were strikingly consistent. Taken together, they suggest that people taking medications such as Ozempic, Wegovy and Mounjaro may develop certain cancers at lower rates than comparable patients who are not taking the drugs — and that those already diagnosed may experience a slower decline and better outcomes. (Source: washingtonpost.com)

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3. Anthropic is calling for top artificial intelligence labs to weigh slowing the pace of development, suggesting that AI systems are advancing so rapidly that they may soon be able to improve themselves without human intervention in ways that could pose significant societal risks. The ability to slow global AI development would “likely be a good thing,” the company said Thursday in a blog post that disclosed internal data documenting how quickly its most advanced models are improving. The post, written by the head of its internal research institute and a company co-founder, noted that model advances appear to be on a path toward “recursive self-improvement,” when AI systems can improve on their own without human intervention. Some AI insiders have seen that threshold as a potential marker of danger and enormous societal upheaval. “We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology,” the post, written by Marina Favaro and Jack Clark, says. (Source: wsj.com)

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4. From Anthropic’s blog post:

If technical trends in advancing capabilities continue, and AI systems are able to develop the capabilities inherent to transformative human ingenuity, then it is plausible that AI systems could design and refine themselves.

In this world, the pace of progress in AI development becomes determined entirely by the availability of compute (or the speed of discovering various efficiencies in algorithmic training or inference) for AI systems. Humans play a substantially diminished role in their development, likely moving most of our effort towards oversight, validation, and verification of an expanding “virtual lab” run by AI systems. We expect that systems capable of automated AI research and development would have skills that would transfer to the rest of science, allowing them to begin to revolutionize other fields.

How the alignment problem gets solved—or not—in this future is something we are least certain about. Models could prove to be sufficiently aligned and capable enough of research taste that they discover and implement novel solutions that we have not yet reached. They could also be sufficiently wise to halt development if not. Alternatively, the rare occurrences of misalignment present in today’s models could compound as the models build their successors, growing more frequent but less understood until we lose control of them. It’s possible that we can’t build, integrate, and verify the tools that we’d need to understand which trendline we are actually on.

We do not have good intuitions for what this world would look like, because our economy is currently driven by humans and human-built tools. By its nature, a world driven by fast recursive self-improvement could become dominated by the self-improving model as its capabilities fully eclipse those of humans and the model proliferates across the broader economy. It is difficult to predict what the economy looks like if human labor stops being competitive. (Source: anthropic.com)