Diabetes drugs may be doing more than managing blood sugar, they could also shape cancer biology in unexpected ways.
The rapid advances in the capabilities of Large Language Models (LLMs) have galvanised public and scientific debates over whether artificial systems might one day be conscious. Prevailing optimism is often grounded in computational functionalism: the assumption that consciousness is determined solely by the right pattern of information processing, independent of the physical substrate. Opposing this, biological naturalism insists that conscious experience is fundamentally dependent on the concrete physical processes of living systems. Despite the centrality of these positions to the artificial consciousness debate, there is currently no coherent framework that explains how biological computation differs from digital computation, and why this difference might matter for consciousness.
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Employing this sensitive assay, we revealed that the integration efficiencies of the 9.9-kb attP-containing DNA donor in rice cells remained remarkably high at 80.5%, relative to the 3.4-kb attP-containing donor, which was set as the baseline for 100% integration efficiency (Figure 2 B). However, a significant decrease in recombination efficiency was observed for donor DNA exceeding 17 kb. The integration efficiency of the 17.4-kb attP-containing plasmid decreased to 42.5% (Figure 2 B), and for the 27.3-kb attP-containing plasmid, it further declined to 8.2% (Figure 2 B). Similar trends were observed in Arabidopsis, with recombination efficiencies of 51.4%, 26.5%, and 9.0% for the 9.9-, 17.4-, and 27.3-kb attP-containing donors, respectively (Figure 2 C). Furthermore, PCR amplification of the attL junctions confirmed that the donor attP sequences had indeed been recombined into the attB as expected (Figures 2 D and 2E). Collectively, these results demonstrate that the Kp03 system can efficiently mediate targeted insertion of large DNA donors up to 27.3 kb in plant cells.
Interestingly, in addition to donor size, we also observed that Kp03-mediated recombination efficiency is sensitive to temperature, exhibiting differential efficiency under varying thermal conditions (Figure S2).
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Despite these potential limitations, Lackenby sees AI’s promise in mathematical hypothesis generation. “So many different areas of mathematics are connected to each other, but spotting new connections is really of interest and this process is a good way of seeing new connections that you couldn’t see before,” he said.
Lackenby’s work demonstrates that AI can be helpful in suggesting conjectures that mathematicians can then go on to prove. And despite Saunders’ reservations, Tao thinks AI could be useful in proving existing conjectures.
The most immediate payoff might not be in tackling the hardest problems but in picking off the lowest-hanging fruit, Tao said.