They really jumped the shark with this one.
Category: robotics/AI – Page 147
Nets wont do it, nets wont cut it, and to me, nets say: we dont know and we sorta give up. We need One System to be able to engage All Types and All Classes of drones, w/ EMF — RF jammers, Microwaves, Lasers, Projectiles, and Missiles. All acting simultaneously, to engage a So Called Drone Swarm.
U.S. Air Force officials at Langley Air Force Base in Virginia are looking at installing anti-drone nets to help protect F-22 Raptor stealth fighters on the flightline. This comes nearly a year after the base was subjected to waves of still-mysterious drone incursions, which The War Zone was first to report. It also underscores the U.S. military’s continued lag when it comes to responding to the very real threats posed by uncrewed aerial systems, at home and aboard, and particular hurdles to doing so domestically.
Langley’s 633rd Contracting Squadron put out a notice on October 4 asking for information about potential counter-drone netting that could be installed around up to 42 existing open-ended sunshade-type shelters at the base. Langley, now technically part of Joint Base Langley-Eustis, is one of a select few bases to host F-22s and is a key component of the Air Force’s posture to defend the U.S. homeland.
The 633rd “is in the process of determining the acquisition strategy to obtain non-personal services for the Unmanned Ariel Services (UAS) Netting for East Ramp Metal Sunshades,” according to the contracting notice. “The intention of the netting is to deter and ultimately prevent the intrusion of UAS’s near airmen and aircraft. This initial sunshade netting installation on the metal sunshade (bay Alpha 1) shall serve as a proof of concept for the remaining sunshades.”
Quantum memory lets a quantum computer perform a task not necessarily with fewer steps, but with less data. Could this in itself be a way to prove quantum advantage?
The new papers show that quantum memory lets a quantum computer perform a task not necessarily with fewer steps, but with less data. As a result, researchers believe this in itself could be a way to prove quantum advantage. “It allows us to, in the more near term, already achieve that kind of quantum advantage,” said Hsin-Yuan Huang, a physicist at Google Quantum AI.
But researchers are excited about the practical benefits too, as the new results make it easier for researchers to understand complex quantum systems.
“We’re edging closer to things people would really want to measure in these physical systems,” said Jarrod McClean, a computer scientist at Google Quantum AI.
Predibase announces the Predibase Inference Engine, their new infrastructure offering designed to be the best platform for serving fine-tuned small language models (SLMs). The Predibase Inference Engine dramatically improves SLM deployments by making them faster, easily scalable, and more cost-effective for enterprises grappling with the complexities of productionizing AI. Built on Predibase’s innovations–Turbo LoRA and LoRA eXchange (LoRAX)–the Predibase Inference Engine is designed from the ground up to offer a best-in-class experience for serving fine-tuned SLMs.
The need for such an innovation is clear. As AI becomes more entrenched in the fabric of enterprise operations, the challenges associated with deploying and scaling SLMs have grown increasingly daunting. Homegrown infrastructure is often ill-equipped to handle the dynamic demands of high-volume AI workloads, leading to inflated costs, diminished performance, and operational bottlenecks. The Predibase Inference Engine addresses these challenges head-on, offering a tailor-made solution for enterprise AI deployments.
Join Predibase webinar on October 29th to learn more about the Predibase Inference Engine!
Seems interesting. But B.D. has fallen behind now, imo.
A new joint research agreement between Boston Dynamics and the Toyota Research Institute combines leading teams in robotics and AI.
Tycho F. A. van der Ouderaa, Mark van der Wilk, Pim de Haan Imperial College London, University of Oxford, & Cusp AI 2024.
https://arxiv.org/abs/2410.08087 https://github.com/tychovdo/noethers-razor
https://twitter.com/tychovdo/status/1846491022227869
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Crazy: Few would argue that Elon Musk is driven. Despite his various detractors, the entrepreneur has built Tesla and SpaceX into major competitors, if not leaders, in their respective industries. This success comes amid various side endeavors like Neuralink and Twitter/X transition. Now, his xAI team has gotten an AI supercluster up and running in just a few weeks.
Elon Musk and his xAI team have seemingly done the impossible. The company built a supercluster of 100,000 Nvidia H200 Blackwell GPUs in only 19 days. Nvidia CEO Jensen Huang called the feat “superhuman.” Huang shared the incredible story in an interview with the Tesla Owners Silicon Valley group on X.
According to Huang, constructing a supercomputer of this size would take most crews around four years – three years in planning and one year on shipping, installation, and operational setup. However, in less than three weeks, Musk and his team managed the entire process – from concept to full functionality. The xAI supercluster even completed its first AI training run shortly after the cluster was powered up.
AI pilots for helicopters.
The US Army’s UH-60M Black Hawk helicopter is set to become autonomous with the integration of a ‘robotic brain,’ enabling pilotless flights.
Tokyo’s Rhymes AI has just released Aria, a free, multimodal AI model that can even do some things that OpenAI can’t.
AI expert Melanie Mitchell shares her take on artificial intelligence—especially what it means to be “intelligent” to begin with.
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Dr. Melanie Mitchell, a leading expert in artificial intelligence, examines the mounting fears surrounding AI, especially as these systems achieve increasingly human-like conversational abilities. She warns that these fears, if unchecked, could lead to overregulation and reduced transparency, making AI less safe and beneficial in the long run.
Mitchell explains that true intelligence, including human intelligence, involves social awareness and understanding the broader impact of actions—capabilities current AI doesn’t have. According to Mitchell, the idea of a superintelligent AI pursuing harmful goals is unrealistic; AI’s capabilities, she says, are still very far from this scenario.