By focusing on the economic opportunities and economic data, fears about AI investment can turn into smart business decisions. There are many paths AI evolution could take. On one end of the spectrum, AI is dismissed as a marginal fad, another bubble fueled by notoriety and misallocated capital. On the other end, it's cast as a dystopian force, destined to eliminate jobs on a large scale and destabilize economies. Markets oscillate between skepticism and the fear of missing out, while the technology itself evolves quickly and investment dollars flow at a rate not seen in decades. All the while, many of today's financial and economic thought leaders hold to the consensus that the financial landscape will stay the same as it has been for the last several years.

Spatiotemporal forecasting on transportation networks is a complex task that requires understanding how traffic nodes interact within a dynamic, evolving system dictated by traffic flow dynamics and social behavioral patterns. The importance of transportation networks and ITS for modern mobility and commerce necessitates forecasting models that are not only accurate but also interpretable, efficient, and robust under structural or temporal perturbations. Recent approaches, particularly Transformer-based architectures, have improved predictive performance but often at the cost of high computational overhead and diminished architectural interpretability. In this work, we introduce Weaver, a novel attention-based model that applies Kronecker product approximations (KPA) to decompose the PN X PN spatiotemporal attention of O(P^2N^2) complexity into local P X P temporal and N X N spatial attention maps. This Kronecker attention map enables our Parallel-Kronecker Matrix-Vector product (P2-KMV) for efficient spatiotemporal message passing with O(P^2N + N^2P) complexity. To capture real-world traffic dynamics, we address the importance of negative edges in modeling traffic behavior by introducing Valence Attention using the continuous Tanimoto coefficient (CTC), which provides properties conducive to precise latent graph generation and training stability. To fully utilize the model's learning capacity, we introduce the Traffic Phase Dictionary for self-conditioning. Evaluations on PEMS-BAY and METR-LA show that Weaver achieves competitive performance across model categories while training more efficiently.

Environment Conservation Ocean Dolphins may be getting an Alzheimer's-like disease due to this neurotoxin The neurotoxins, found in algal blooms, primarily affect the body's nervous system. Breakthroughs, discoveries, and DIY tips sent every weekday. For marine biologists, dolphins are often viewed as sentinel species, or animals that shed light on the health of the ocean . Along with whales, porpoises, and other cetacean species, dolphins are one way that researchers know to sound the alarm about environmental hazards that might affect the ocean as a whole and potentially humans. In this context, researchers have connected neurotoxins from algal blooms to brain changes associated with an Alzheimer's-like disease in dolphins in Florida.

Sign up to receive it in your inbox. Aside from a temporary love, or a new friend, you could easily stumble upon fabulous stage shows that were presented with such seriousness, often, that you wondered if--while watching the amazing Duelling Bankheads, for instance, or so many people who got up so brilliantly as Stevie Nicks on the Night of 1000 Stevies--you were high on the entertainment, or on dancing with your chosen community, or just amazed by what New York had to offer by way of creativity. Looking back, I can see that, for me at least, it was the combination of all three elements together that gave such hope about Manhattan's ability to foster noncommercial glamour, and to support young performers who were trying things out and seeing what stuck. Richard Move as Martha Graham. The shows I loved the most were at Jackie 60, spearheaded by the irreplaceable Chi Chi Valenti and Johnny Dynell, the resident d.j.

Melania Trump Used as'Window-Dressing' in Elaborate Memecoin Fraud, Legal Filing Claims The first lady of the United States became a pawn in an intricate memecoin scam that resulted in millions of dollars in losses, crypto investors have alleged. A cryptocurrency promoted in January by US first lady Melania Trump was part of a sophisticated fraud that "leveraged celebrity association and'borrowed fame' to sell legitimacy to unsuspecting investors," a new legal filing has alleged. In April, crypto investors brought a federal class action lawsuit against Benjamin Chow, cofounder of crypto exchange Meteora, and Hayden Davis, cofounder of crypto venture capital firm Kelsier Labs, among other defendants, accusing them of a multimillion-dollar fraud involving a single memecoin, $M3M3. Later, the plaintiffs filed an amended complaint, expanding the allegations to include racketeering activity. They claimed the pair had colluded to rig the market for $LIBRA, a coin promoted by Javier Milei, president of Argentina, which collapsed in value shortly after launch.

How healthy am I? My immunome knows the score. Groundbreaking new tests reveal patterns in our immune systems that can signal underlying disease and tell us how well we might recover from our next cold. I got my results in a text message. It's not often you get a text about the robustness of your immune system, but that's what popped up on my phone last spring. Sent by John Tsang, an immunologist at Yale, the text came after his lab had put my blood through a mind-boggling array of newfangled tests. The result--think of it as a full-body, high-resolution CT scan of my immune system--would reveal more about the state of my health than any test I had ever taken. And it could potentially tell me far more than I wanted to know. "David," the text read, "you are the red dot." Tsang was referring to an image he had attached to the text that showed a graph with a scattering of black dots representing other people whose immune systems had been evaluated--and a lone red one.

Demand for AI chips is booming--and so is the need for software to run them. Chris Lattner's startup Modular just raised $250 million to build the best developer tools for AI hardware. At a certain point between building Apple's developer tools, leading a core part of Google's AI infrastructure team, and clashing with Elon Musk during a stint as Tesla's Autopilot chief, Chris Lattner's vision for his life's work started to come into focus. AI was taking over the world, and demand was growing for the chips that powered it. But the software stack for those chips was dominated by just a few big companies.

Actress, entrepreneur, and model Christie Brinkley joins'Fox & Friends' to discuss her new memoir "Uptown Girl," which reflects on her early life, marriages, and career in the public eye. Christie Brinkley and her daughter Sailor Brinkley-Cook have plenty in common despite their 44-year difference. The supermodel, 71, recently appeared on Kristin Davis' "Are You a Charlotte?" Both women were shocked by the results. "[Sailor] said, 'Mom, you're right not to go on [dating apps] because the same guys that, you know, said yes to me are saying yes to you,'" the Sports Illustrated Swimsuit model revealed.

The origins of the colors of Trans-Neptunian Objects (TNOs) represent a crucial unresolved question, central to understanding the history of our Solar System. Recent observational surveys have revealed correlations between the eccentricity and inclination of TNOs and their colors. This has rekindled the long-standing debate on whether these colors reflect the conditions of TNO formation or their subsequent collisional evolution. In this study, we address this question with 98.7% certainty, using a model-agnostic, data-driven approach based on causal graphs. First, as a sanity check, we demonstrate how our model can replicate the currently accepted paradigms of TNOs' dynamical history, blindly and without any orbital modeling or physics-based assumptions. In fact, our causal model (with no knowledge of the existence of Neptune) predicts the existence of an unknown perturbing body, i.e., Neptune. We then show how this model predicts, with high certainty, that the color of TNOs is the root cause of their inclination distribution, rather than the other way around. This strongly suggests that the colors of TNOs reflect an underlying dynamical property, most likely their formation location. Moreover, our causal model excludes formation scenarios that invoke substantial color modification by subsequent irradiation. We therefore conclude that the colors of TNOs are predominantly primordial.