Poodle crossbreeds have grown overwhelmingly popular, sparking controversy in dog parks and kennel clubs alike. The features of doodles such as Peaches (above), a goldendoodle, have become the canine equivalent of Instagram face. Meet the Breeds, the American Kennel Club's annual showcase of purebred dogs, took place over two eye-wateringly cold days in early February at the Javits Center, in Manhattan. About a hundred and fifty of the two hundred and five varieties recognized as official breeds by the A.K.C., the long-standing authority in the U.S. dog world, were in attendance for the public to ogle, fondle, and coo "So cute!" to, including the basset fauve de Bretagne, a hunting hound from France that's one of three newly recognized breeds recently allowed into the purebred pantheon. Some of the dogs had competed in the Westminster Kennel Club Dog Show earlier in the week, and past champions had their ribbons on display. In spite of the frigid weather, pavilions hosting the more popular breeds--the pug, the Doberman pinscher, the Great Dane, the St. Bernard--were packed. Lesser-known varieties, such as the saluki, the Löwchen, and the Lapponian herder, drew sparser crowds. There were exhibition spaces for each breed, and on the back walls were three adjectives supposedly describing that particular type of dog's temperament. There is, in fact, no evidence that temperament is consistent within a breed, but the idea is deeply rooted in dogdom. I stopped to caress the velvety ear leather of a pharaoh hound ("Friendly, Smart, Noble"), a sprinting breed once used to hunt rabbits in Malta; accept kisses from a Portuguese water dog, bred to assist with retrieving tackle ("Affectionate, Adventurous, Athletic"); and have my photograph taken with a Leonberger, a German breed from the town of Leonberg, in southwest Germany ("Friendly, Gentle, Playful"). No one was supposed to be openly selling dogs, but, if you asked, the breeders would share their information. Excluding what are known as companion dogs, like the Leonberger, most of the animals at the show were designed for a purpose that is no longer required of them. In Great Britain, foxhounds are legally barred from chasing foxes. Consider the fate of the otterhound, an ancient variety with a noble heritage which was once used in the U.K. to hunt river otters, which were prized for their thick fur and disliked by wealthy landowners because they ate fish in their stocked ponds.

Coordinating the motion of robots with high degrees of freedom (DoF) to grasp objects gives rise to many challenges. In this paper, we propose a novel imitation learning approach to learn a policy that directly predicts 23 DoF grasp trajectories from a partial point cloud provided by a single, fixed camera. At the core of the approach is a second-order geometric-based model of behavioral dynamics. This Neural Geometric Fabric (NGF) policy predicts accelerations directly in joint space. We show that our policy is capable of generalizing to novel objects, and combine our policy with a geometric fabric motion planner in a loop to generate stable grasping trajectories. We evaluate our approach on a set of three different objects, compare different policy structures, and run ablation studies to understand the importance of different object encodings for policy learning.

China this week chose not to sign onto an international "blueprint" agreed to by some 60 nations, including the U.S., that looked to establish guardrails when employing artificial intelligence (AI) for military use. More than 90 nations attended the Responsible Artificial Intelligence in the Military Domain (REAIM) summit hosted in South Korea on Monday and Tuesday, though roughly a third of the attendees did not support the nonbinding proposal. AI expert Arthur Herman, senior fellow and director of the Quantum Alliance Initiative with the Hudson Institute, told Fox News Digital that the fact some 30 nations opted out of this important development in the race to develop AI is not necessarily cause for concern, though in Beijing's case it is likely because of its general opposition to signing multilateral agreements. Participants are shown prior to the closing session of the REAIM summit in Seoul, South Korea, on Sept. 10, 2024. "What it boils down to … is China is always wary of any kind of international agreement in which it has not been the architect or involved in creating and organizing how that agreement is going to be shaped and implemented," he said.

China has once again extended its policy of censorship and surveillance as it looks to keep artificial intelligence (AI) models in check even as it races to advance the ever-expanding technology. The Chinese Communist Party (CCP) has introduced more regulative measures to make sure its home-based tech companies adhere to the party's ideological rules. All AI firms are required to participate in a government review which analyzes the companies' large language models (LLMs) to ensure they "embody core socialist values," as first reported by the Financial Times last week. A man walks past a photo of Chinese President Xi Jinping at the Museum of the Communist Party of China in Beijing on March 3, 2023. A NEW BREED OF MILITARY AI ROBO-DOGS COULD BE MARINES' NEW SECRET WEAPON China has long worked to suppress information accessible over the internet through the use of its "Great Firewall" -- which has been used to block a litany of items perceived as bad for the CCP, such as information surrounding the 1989 Tiananmen Square massacre or memes comparing Chinese President Xi Jinping to Winnie the Pooh.

We introduce a new amortized likelihood ratio estimator for likelihood-free simulation-based inference (SBI). Our estimator is simple to train and estimates the likelihood ratio using a single forward pass of the neural estimator. Our approach directly computes the likelihood ratio between two competing parameter sets which is different from the previous approach of comparing two neural network output values. We refer to our model as the direct neural ratio estimator (DNRE). As part of introducing the DNRE, we derive a corresponding Monte Carlo estimate of the posterior. We benchmark our new ratio estimator and compare to previous ratio estimators in the literature. We show that our new ratio estimator often outperforms these previous approaches. As a further contribution, we introduce a new derivative estimator for likelihood ratio estimators that enables us to compare likelihood-free Hamiltonian Monte Carlo (HMC) with random-walk Metropolis-Hastings (MH). We show that HMC is equally competitive, which has not been previously shown. Finally, we include a novel real-world application of SBI by using our neural ratio estimator to design a quadcopter. Code is available at https://github.com/SRI-CSL/dnre.

On Thursday, jurors convicted former crypto mogul Sam Bankman-Fried of defrauding his customers out of as much as $10 billion. He will likely spend the rest of his 30s--and possibly his 40s, 50s, and 60s--in prison. The judge is expected to sentence him in March. As former confidants and close friends testified against him during his monthlong trial, Bankman-Fried's parents, Joseph and Barbara, showed up day after day to support their son, whose crypto exchange FTX imploded late last year. The Stanford Law professors' hand gestures and facial expressions played prominently into journalists' recounts of the proceedings, offering the real-life version of the cutaway shot integral to any courtroom TV show.

Teachers are a creative bunch. They have to be to come up with lesson plans and exams that help students grow their minds and prevent those same students from relying too much on technology to enhance their work or to cheat. Which is why the rollout of OpenAI's ChatGPT has many teachers worried. The chatbot can answer almost any type of question, even if the answers aren't always accurate. Marketplace's Kimberly Adams spoke with Daniel Herman, an English teacher at Maybeck High School in Berkeley, California.

If you've been on social media lately, you've doubtless encountered fictional stories and essays generated by "ChatGPT," an artificial intelligence program that can generate remarkably solid pieces of prose in response to prompts both serious and whimsical, and can do so instantly and in any imaginable style. Others, mostly writers and teachers, are filled with existential dread. "My life--and the lives of thousands of other teachers and professors, tutors and administrators--is about to drastically change," wrote English teacher Daniel Herman in The Atlantic. My hunch is that's a lot less true than he thinks. For starters, let's immediately dispense with the idea that artificial intelligence will make writing instruction obsolete.

A virtual, autonomous racing challenge launching this week will enable aspiring racers to head to the track without building a car, knowing how to brake and accelerate through a corner, or leaving their computer. And as teams tackle the demands of high-speed and safe driving that pushes race cars to their limits, they will improve the safety of autonomous vehicles and the learning algorithms teaching them to drive. The Learn-to-Race Autonomous Racing Virtual Challenge started Monday, Dec. 6. Competitors use the Learn-to-Race environment to teach an artificially intelligent agent how to race. The challenge is coupled with a workshop on Safe Learning for Autonomous Driving, which is accepting research paper submissions.

On the second day of the COSM 2021 conference, speakers asked -- with appropriate skepticism -- whether we could ever produce true Artificial General Intelligence (AGI). But the final day of the conference hosted a conversation on the realistically achievable forms of AI and quantum computing that may pose existential threats to modern life. Robert J. Marks, Director of the Walter Bradley Center for Natural and Artificial Intelligence (which hosted COSM) -- also Distinguished Professor of Electrical and Computer Engineering at Baylor University -- spoke first. The title of his 2020 book, The Case for Killer Robots: Why America's Military Needs to Continue Development of Lethal AI, provides an unsubtle hint at his position. Marks thinks that AI will never be "will never be sentient. It will never understand what it is doing. And, currently, it has no common sense."