The popularity of commercial nuclear reactors has surged in recent years as worries about climate change and energy independence drowned out concerns about meltdowns and radioactive waste. The problem is, building nuclear power plants is expensive and slow. A new generation of nuclear power technology could reinvent what a reactor looks like--and how it works. Advocates hope that new tech can refresh the industry and help replace fossil fuels without emitting greenhouse gases. Here's what that might look like . Next-gen nuclear is one of our 10 Breakthrough Technologies this year.

Astrophysicist Stephen Hawking told Last Week Tonight's John Oliver a chilling but memorable hypothetical story a decade ago about the potential dangers of AI. The gist is a group of scientists build a superintelligent computer and ask it, "Is there a God?" The computer answers, "There is now" and a bolt of lightning zaps the plug preventing it from being shut down. Let's hope that's not what happened with OpenAI and some missing evidence from the New York Times' plagiarism lawsuit. Wired reported that a court declaration filed by the New York Times on Wednesday says that OpenAI's engineers accidentally erased evidence of the AI's training data that took a long time to research and compile.

The report, which describes the lengths OpenAI, Google and Meta have gone to in order to maximize the amount of data they can feed to their AIs, cites numerous people with knowledge of the companies' practices. It comes just days after YouTube CEO Neal Mohan said in an interview with Bloomberg Originals that OpenAI's alleged use of YouTube videos to train its new text-to-video generator, Sora, would go against the platform's policies. According to the NYT, OpenAI used its Whisper speech recognition tool to transcribe more than one million hours of YouTube videos, which were then used to train GPT-4. The Information previously reported that OpenAI had used YouTube videos and podcasts to train the two AI systems. OpenAI president Greg Brockman was reportedly among the people on this team.

The New York Times reports that Israel's military intelligence has been using an experimental facial recognition program in Gaza that's misidentified Palestinian civilians as having ties to Hamas. Google Photos allegedly plays a part in the chilling program's implementation, although it appears not to be through any direct collaboration with the company. The surveillance program reportedly started as a way to search for Israeli hostages in Gaza. However, as often happens with new wartime technology, the initiative was quickly expanded to "root out anyone with ties to Hamas or other militant groups," according to The NYT. The technology is flawed, but Israeli soldiers reportedly haven't treated it as such when detaining civilians flagged by the system.

Unsupervised clustering is widely used to explore large corpora, but existing formulations neither consider the users' goals nor explain clusters' meanings. We propose a new task formulation, "Goal-Driven Clustering with Explanations" (GoalEx), which represents both the goal and the explanations as free-form language descriptions. For example, to categorize the errors made by a summarization system, the input to GoalEx is a corpus of annotator-written comments for system-generated summaries and a goal description "cluster the comments based on why the annotators think the summary is imperfect.''; the outputs are text clusters each with an explanation ("this cluster mentions that the summary misses important context information."), which relates to the goal and precisely explain which comments should (not) belong to a cluster. To tackle GoalEx, we prompt a language model with "[corpus subset] + [goal] + Brainstorm a list of explanations each representing a cluster."; then we classify whether each sample belongs to a cluster based on its explanation; finally, we use integer linear programming to select a subset of candidate clusters to cover most samples while minimizing overlaps. Under both automatic and human evaluation on corpora with or without labels, our method produces more accurate and goal-related explanations than prior methods. We release our data and implementation at https://github.com/ZihanWangKi/GoalEx.

How they did it: The team asked language models where they stand on various topics, such as feminism and democracy. They used the answers to plot them on a political compass, then tested whether retraining models on even more politically biased training data changed their behavior and ability to detect hate speech and misinformation (it did). Why it matters: As AI language models are rolled out into products and services used by millions, understanding their underlying political assumptions could not be more important. That's because they have the potential to cause real harm. A chatbot offering health-care advice might refuse to offer advice on abortion or contraception, for example.

To keep our bodies at their relatively stable core temperature of around 98.6 F (37 C), we constantly lose heat. It's a process that can be sped up by sweating. But the whole balancing act can get derailed when we're exposed to extreme heat. If your body isn't able to cool itself down fast enough, a whole cascade of problems can start, from stressing out your heart to throwing your kidneys and liver into chaos. Here's some good news: to some extent, our bodies can and do adjust slightly to the heat.

Campus Reform correspondents Wyatt Eichholz and Kale Ogunbor joined'Fox & Friends First' to discuss the impact of woke culture on college campuses. Liberal media figures and professors mocked and attacked the New York Times Wednesday for publishing a guest essay from a conservative Ivy League student criticizing his campus' progressive attitude. The essay "My Liberal Campus Is Pushing Freethinkers to the Right" came from Princeton University senior Adam S. Hoffman who described his fellow campus conservatives as growing increasingly more right-wing in backlash to their college's more leftist stances. "Today's campus conservatives embrace a less moderate, complacent and institutional approach to politics. Instead of belief in the status quo, many tend toward scorched-earth politics. But these changes aren't solely the consequence of a fractured national politics," Hoffman wrote.

Complementary to finding good general word embeddings, an important question for representation learning is to find dynamic word embeddings, e.g., across time or domain. Current methods do not offer a way to use or predict information on structure between sub-corpora, time or domain and dynamic embeddings can only be compared after post-alignment. We propose novel word embedding methods that provide general word representations for the whole corpus, domain-specific representations for each sub-corpus, sub-corpus structure, and embedding alignment simultaneously. We present an empirical evaluation on New York Times articles and two English Wikipedia datasets with articles on science and philosophy. Our method, called Word2Vec with Structure Prediction (W2VPred), provides better performance than baselines in terms of the general analogy tests, domain-specific analogy tests, and multiple specific word embedding evaluations as well as structure prediction performance when no structure is given a priori. As a use case in the field of Digital Humanities we demonstrate how to raise novel research questions for high literature from the German Text Archive.

Exactly two weeks after Russia invaded Ukraine in February, Alexander Karp, the CEO of data analytics company Palantir, made his pitch to European leaders. With war on their doorstep, Europeans ought to modernize their arsenals with Silicon Valley's help, he argued in an open letter. Militaries are responding to the call. NATO announced on June 30 that it is creating a $1 billion innovation fund that will invest in early-stage startups and venture capital funds developing "priority" technologies, while the UK has launched a new AI strategy specifically for defense, and the Germans have earmarked just under half a billion for research and AI. The war in Ukraine has added urgency to the drive to push more AI tools onto the battlefield. Those with the most to gain are startups such as Palantir, which are hoping to cash in as militaries race to update their arsenals with the latest technologies.