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Egyptian President Abdel Fattah el-Sisi is coming under increasing pressure to take a stronger stance on the atrocities unfolding in Gaza. It has take the Egyptian leader months to condemn Israel's actions and he has held firm to the view that Egypt “will not be a gateway for the displacement of the Palestinian people”. A $USD35 billion gas deal with Israel may hold some clues to the complicated relationship between the two countries.
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The AP team will wear formal Tevas to the new White House ballroom. Otherwise, in this week’s news: Danny and Derek reflect on the 80th anniversary of the US dropping the atomic bomb on Hiroshima (1:46); in Israel-Palestine, Netanyahu announces his “full occupation” plan (8:24) as the US expands the Gaza Humanitarian Foundation (13:58); the Lebanese government moves to disarm Hezbollah (16:48); the US looks to host an Armenia-Azerbaijan peace summit (20:51); Trump punishes India for purchasing Russian oil (24:20); Thailand and Cambodia agree to the deployment of ceasefire monitors (27:49); in Sudan, the RSF carries out a new atrocity (29:50) and the military accuses the United Arab Emirates of hiring mercenaries (32:37); a new report details sexual violence in the Tigray Region of Ethiopia (35:06); in Russia-Ukraine, Steve Witkoff visits Moscow ahead of a Putin-Trump meeting (37:28) as the US nevertheless plans to impose tariffs on Russia (40:34); El Salvador’s legislature removes presidential term limits (41:57); and in US news, America makes a new “third country” trafficking agreement with Rwanada (43:15), the State Department starts a new program forcing travelers to pay bonds to the US government (45:23), and NASA plans to put a nuclear reactor on the Moon (46:50).
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Biology is an area of science where AI and machine-learning approaches have seen some spectacular successes, such as designing enzymes to digest plastics and proteins to block snake venom. But in an era of seemingly endless AI hype, it might be easy to think that we could just set AI loose on the mounds of data we've already generated and end up with a good understanding of most areas of biology, allowing us to skip a lot of messy experiments and the unpleasantness of research on animals.
But biology involves a whole lot more than just protein structures. And it's extremely premature to suggest that AI can be equally effective at handling all aspects of biology. So we were intrigued to see a study comparing a set of AI software packages designed to predict how active genes will be in cells exposed to different conditions. As it turns out, the AI systems couldn't manage to do any better than a deliberately simplified method of predicting.
The results serve as a useful caution that biology is incredibly complex, and developing AI systems that work for one aspect of it is not an indication that they can work for biology generally.
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