Meta to track workers' clicks and keystrokes to train AI Meta will start tracking the way employees work, including their keystrokes and mouse clicks, to train its artificial intelligence (AI) models. The company, which owns Instagram and Facebook, told workers on Tuesday that a new tool will run on Meta's computers and internal apps, logging their activity to be used as training data for AI technology. A Meta spokesman told the BBC: If we're building agents to help people complete everyday tasks using computers, our models need real examples of how people actually use them. The data is not used for any other purpose, he said, adding that the tool has safeguards in place to protect sensitive content. But one Meta employee, who asked not to be identified, said having their smallest actions on a computer being used to train AI model as workers expect a slew of additional job cuts feels very dystopian.

Do the Dodgers get an unfair advantage with'bizarre' rule impacting Shohei Ohtani? Florida's Thomas Haugh ditches Draft to return to school amid swirling Todd Golden rumors Mamdani takes'Curse of the Mambino' on the chin as Mets' 11-game skid sets franchise record Cubs' co-owner pushes back on woke backlash Matt Shaw received for attending Charlie Kirk's memorial'Zig-Zag Theory': Houston Rockets will cover and even series vs. Los Angeles Lakers in Game 2 Stephen A. Smith says he believes Dianna Russini and Mike Vrabel are innocent -- for now Wisconsin teen's turkey hunt takes a wild turn when a bobcat lunges and grabs his arm on camera Matt Fitzpatrick is the king of Harbour Town, lame USA chants, and LIV Golf's telling announcement Dana Perino: Economic pressure on Iranian regime is'excruciating' IRGC's'extreme commanders' abused Iranian people for decades: Ret Lt Col Chuck DeVore Missing scientists probe was reportedly sparked after'UFO General' disappeared Iranian leaders say they don't negotiate'under the shadow of threats' VP Vance's Pakistan trip suspended as Trump weighs diplomacy vs force on Iran Former Virginia governor condemns Dem redistricting plan as'illegal power grab' California Dems warned of'blue Armageddon' in governor race This is how the US can'pressure' the Iranian regime: Former leading CENTCOM official Democratic Senate candidate criticized for remarks about JD Vance's family A stretcher crew stood by but there wasn't much left to carry off after the robot's wild self-destruction A humanoid robot, 'Lightning,' shattered the Beijing half-marathon world record this weekend, completing the race in just 50 minutes and 26 seconds, 13 miles faster than any human. Cyber expert Kurt Knutsson warns this massive leap in artificial intelligence, along with Tesla's Optimus robot, necessitates a universal'off button' and stronger guardrails to ensure safety and prevent future human replacement. I'm equally excited and terrified by it. On one hand, I'd love to have a robot around the house so it could fold my laundry and make me feel like George Jetson.

Trump EXTENDS Iran ceasefire again as he backs off bombing threat amid chaos among'seriously fractured' Tehran leadership Anna Kepner's stepbrother skips court appearance as prosecutors fight to put him behind bars amid rape and murder charges New'Hollywood dose' pill: A-listers hooked on'youth elixir' that dermatologists say is anti-aging, shrinks pores, smooths wrinkles... and even banishes rosacea Truth about your Mounjaro injection site: Our expert doctors reveal exactly where you should inject yourself for the best results, what to do if your weight loss has slowed down... and the areas you should NEVER jab Driver who hit and killed jogger father-of-two sues victim's estate claiming incident left him with severe PTSD World Series winner and MLB great Garret Anderson's cause of death revealed after his sudden passing at 53 Sydney Sweeney's role is cut from The Devil Wears Prada 2 Alarm over popular new coffee chain invading the US... as experts warn of chilling secret behind its $1.99 brew Days after we got engaged, the love of my life told me he'd killed a man and buried him in a bog. I reported him to police... but then I made this irreversible mistake Ark of the Covenant's final resting place pinpointed by archaeologists as fresh search begins Wealthy realtor, 86, who'loved the finer things' disappeared into California desert after fight with daughter and grandson... then a livestreamer made horrific discovery at beauty spot Life-threatening cantaloupe recall in four states upgraded to FDA's highest risk level... 'reasonable probability of death' MORE: Death of Air Force whistleblower set to reveal UFO secrets declared'suspicious' One of the leading voices pushing for UFO disclosure has made a shocking connection between an ancient biblical text and the existence of alien life. Congresswoman Anna Paulina Luna of Florida recently posted two cryptic messages on X, one telling people to'Read the book of Enoch' and the other displaying the 15th-century painting nicknamed the ' Madonna of the UFO.' It is the latest reference the chairwoman of the House Oversight Committee's hearings on UFOs has made to the Book of Enoch while speaking about extraterrestrials and alien spacecraft. The book is an ancient Jewish religious text, written in stages between 300 and 100 BC, attributed to the biblical figure Enoch, the great-grandfather of Noah.

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Neural Information Processing Systems http://nips.cc/

In this paper we present a practical solution with performance guarantees to the problem of dimensionality reduction for very large scale sparse matrices. We show applications of our approach to computing the Principle Component Analysis (PCA) of any n dmatrix, using one pass over the stream of its rows. Our solution uses coresets: a scaled subset of the n rows that approximates their sum of squared distances to every k-dimensional affine subspace. An open theoretical problem has been to compute such a coreset that is independent of both n and d. An open practical problem has been to compute a non-trivial approximation to the PCA of very large but sparse databases such as the Wikipedia document-term matrix in a reasonable time. We answer both of these questions affirmatively. Our main technical result is a new framework for deterministic coreset constructions based on a reduction to the problem of counting items in a stream.

We consider the problem of Robust PCA in the fully and partially observed settings. Without corruptions, this is the well-known matrix completion problem. From a statistical standpoint this problem has been recently well-studied, and conditions on when recovery is possible (how many observations do we need, how many corruptions can we tolerate) via polynomial-time algorithms is by now understood. This paper presents and analyzes a non-convex optimization approach that greatly reduces the computational complexity of the above problems, compared to the best available algorithms. In particular, in the fully observed case, with r denoting rank and d dimension, we reduce the complexity from O(r2d2 log(1/ε)) to O(rd2 log(1/ε)) - a big savings when the rank is big. For the partially observed case, we show the complexity of our algorithm is no more than O(r4dlog dlog(1/ε)). Not only is this the best-known run-time for a provable algorithm under partial observation, but in the setting where r is small compared to d, it also allows for near-linear-in-drun-time that can be exploited in the fully-observed case as well, by simply running our algorithm on a subset of the observations.

In this paper, we develop a novel homotopy smoothing (HOPS) algorithm for solving a family of non-smooth problems that is composed of a non-smooth term with an explicit max-structure and a smooth term or a simple non-smooth term whose proximal mapping is easy to compute. The best known iteration complexity for solving such non-smooth optimization problems is O(1/) without any assumption on the strong convexity. In this work, we will show that the proposed HOPS achieved a lower iteration complexity of O(1/1 θ) 1with θ (0,1] capturing the local sharpness of the objective function around the optimal solutions. To the best of our knowledge, this is the lowest iteration complexity achieved so far for the considered non-smooth optimization problems without strong convexity assumption. The HOPS algorithm employs Nesterov's smoothing technique and Nesterov's accelerated gradient method and runs in stages, which gradually decreases the smoothing parameter in a stage-wise manner until it yields a sufficiently good approximation of the original function. We show that HOPS enjoys a linear convergence for many well-known non-smooth problems (e.g., empirical risk minimization with a piece-wise linear loss function and `1 norm regularizer, finding a point in a polyhedron, cone programming, etc). Experimental results verify the effectiveness of HOPS in comparison with Nesterov's smoothing algorithm and the primal-dual style of first-order methods.

Neural Information Processing Systems http://nips.cc/

People often learn from others' demonstrations, and inverse reinforcement learning (IRL) techniques have realized this capacity in machines. In contrast, teaching by demonstration has been less well studied computationally. Here, we develop a Bayesian model for teaching by demonstration. Stark differences arise when demonstrators are intentionally teaching (i.e.