The ENL metric measures the smoothness in the homogeneous regions.

Motivated by a recent literature on the double-descent phenomenon in machine learning, we consider highly over-parameterized models in causal inference, including synthetic control with many control units.

Moltbook Is a Social Network for AI Bots. Pillay is an editorial fellow at TIME. In this photo illustration, a smartphone displays the Moltbook website homepage. In this photo illustration, a smartphone displays the Moltbook website homepage. Pillay is an editorial fellow at TIME.

Confirming which users are kids is politically fraught and a technical nightmare. Here's what moves from OpenAI and the FTC tell us. How do tech companies check if their users are kids? This question has taken on new urgency recently thanks to growing concern about the dangers that can arise when children talk to AI chatbots. For years Big Tech asked for birthdays (that one could make up) to avoid violating child privacy laws, but they weren't required to moderate content accordingly. Two developments over the last week show how quickly things are changing in the US and how this issue is becoming a new battleground, even among parents and child-safety advocates.

How Does the Hive Mind Work in? The "Joining" seems to connect people via radio waves. Let's dig into the physics at play. Carol Sturka (left) and her chaperone," Zosia, in the Apple TV show . You know what's great about a show like?

'In the Gaza Strip, we know that this massive trove of intercepted phone calls was used in airstrikes that killed civilians.' 'Data is control': what we learned from a year investigating the Israeli military's ties to big tech'In the Gaza Strip, we know that this massive trove of intercepted phone calls was used in airstrikes that killed civilians.' I n January this year, Harry Davies and Yuval Abraham first reported that Microsoft had deepened its ties to Israel alongside other major tech firms. Since then, the Guardian has published an award-winning series of investigations - in partnership with the Israeli-Palestinian publication +972 Magazine and the Hebrew-language outlet Local Call - that has revealed a symbiotic relationship between Silicon Valley and the Israeli military. One investigation exposed an Israeli mass surveillance program scooping up virtually all Palestinian phone calls and storing them on Microsoft's cloud services - setting off an inquiry that ultimately prompted the company to cut off Israel's access to some of its technology.

\noindent Hyper-parameter selection is a central practical problem in modern machine learning, governing regularization strength, model capacity, and robustness choices. Cross-validation is often computationally prohibitive at scale, while fully Bayesian hyper-parameter learning can be difficult due to the cost of posterior sampling. We develop a generative perspective on hyper-parameter tuning that combines two ideas: (i) optimization-based approximations to Bayesian posteriors via randomized, weighted objectives (weighted Bayesian bootstrap), and (ii) amortization of repeated optimization across many hyper-parameter settings by learning a transport map from hyper-parameters (including random weights) to the corresponding optimizer. This yields a ``generator look-up table'' for estimators, enabling rapid evaluation over grids or continuous ranges of hyper-parameters and supporting both predictive tuning objectives and approximate Bayesian uncertainty quantification. We connect this viewpoint to weighted $M$-estimation, envelope/auxiliary-variable representations that reduce non-quadratic losses to weighted least squares, and recent generative samplers for weighted $M$-estimators.

My position feels more precarious than ever. It's a question that I sometimes toss out in the company of friends who--like me, and maybe like you--have a complicated relationship to their job. I've worked at WIRED as a writer for eight years, and with much success. Eight years is also an eternity in news media, and especially if you are Black. All industries suffer from unique growing pains. Ours just so happens to have laughably high turnover rates, a distaste for racial and gender diversity, and the dubious distinction of being perpetually on the verge of extinction. So on nights when friends and I gather, trading war stories of workplace microaggressions and corporate mismanagement under damp bar lighting, we wonder how we've lasted as long as we have. The only reason I've survived, I joke, is because I'm Black. It's a silly thing to say, particularly because I have no actual proof of it other than the occasional feeling. What I do know is that I've been The Only One in more spaces than I care to remember, and rarely by choice.