Thanks for this excellent suggestion which makes the paper stronger! We now clarify the difference between "high-level strategy" and "decision rule" (for We now discuss this point in the main paper and show the simulations in the appendix. R3: A closer analysis of error differences would be helpful. Top row: "Hard" images for CNNs (correctly classified by all humans but not by any SF.8, SF.9); now linked & discussed more prominently.

Some years ago, the satellite radio and pharmaceutical entrepreneur Martine Rothblatt decided that she wanted a semblance of her wife to last forever. So she commissioned Hanson Robotics to create a robot that looked exactly like the head and shoulders of her wife, Bina. The human Bina uploaded many of her memories and autobiographical material into a computer connected to the robot, which Rothblatt named BINA 48. Other information about the world was also uploaded. Like ChatGPT, BINA 48 has a large database (although not as extensive) and a search engine.

AI has officially taken over the world. Depending on who you ask, ChatGPT and Midjourney are saviour of work, art, journalism, law and ethics – or the destroyer of them. Right now, consumer AI is in no man's land, with computer-generated art mostly showing us how Mr Blobby would fare in the Napoleonic Wars. But that hasn't stopped AI start-ups from securing big money investment, and websites using ChatGPT to create personalised content. Which got me thinking: if multi-million dollar companies can wrangle AI to lighten their workloads, why can't I? If'real' jobs will be made obsolete once the machines take over, why resist it?

What do anti-vaxxers and anti-GMO campaigners have in common? Underpinning both "antis" is a shared belief that because vaccines and GMOs are "unnatural," they're bad, which for many people--whatever their feelings about vaccines and GMOs--segues into its inverse: What's natural is good. Given a choice, most people gravitate toward the natural over the artificial. After all, natural environments are preferable to garbage dumps, natural foods are nearly always healthier than stuff concocted in a chemistry lab. Yet it needs to be said loud and clear: Just because something is natural doesn't mean it's good.

For a quality conversation between a human and a machine, responses have to be quick, intelligent and natural-sounding. But up to now, developers of language-processing neural networks that power real-time speech applications have faced an unfortunate trade-off: Be quick and you sacrifice the quality of the response; craft an intelligent response and you're too slow. That's because human conversation is incredibly complex. Every statement builds on shared context and previous interactions. From inside jokes to cultural references and wordplay, humans speak in highly nuanced ways without skipping a beat.