From paged attention, continuous batching, prefix caching, specdec, etc. to multi-GPU, multi-node dynamic serving at scale.
Category: robotics/AI – Page 7
Researchers pioneer optical generative models, ushering in a new era of sustainable generative AI
In a major leap for artificial intelligence (AI) and photonics, researchers at the University of California, Los Angeles (UCLA) have created optical generative models capable of producing novel images using the physics of light instead of conventional electronic computation.
Published in Nature, the work presents a new paradigm for generative AI that could dramatically reduce energy use while enabling scalable, high-performance content creation.
Generative models, including diffusion models and large language models, form the backbone of today’s AI revolution. These systems can create realistic images, videos, and human-like text, but their rapid growth comes at a steep cost: escalating power demands, large carbon footprints, and increasingly complex hardware requirements. Running such models requires massive computational infrastructure, raising concerns about their long-term sustainability.
AI Insiders Reveal Elon Musk’s Master Plan to Win AI w/ AWG & Dave Blundin
Peter H. Diamandis
Deep learning method enables efficient Boltzmann distribution sampling across a continuous temperature range
A research team has developed a novel direct sampling method based on deep generative models. Their method enables efficient sampling of the Boltzmann distribution across a continuous temperature range. The findings have been published in Physical Review Letters. The team was led by Prof. Pan Ding, Associate Professor from the Departments of Physics and Chemistry, and Dr. Li Shuo-Hui, Research Assistant Professor from the Department of Physics at the Hong Kong University of Science and Technology (HKUST).
DNA-based neural network learns from examples to solve problems
Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead of electronic parts that carries out computation through chemical reactions rather than digital signals.
An important property of any neural network is the ability to learn by taking in information and retaining it for future decisions. Now, researchers in the laboratory of Lulu Qian, professor of bioengineering, have created a DNA-based neural network that can learn. The work represents a first step toward demonstrating more complex learning behaviors in chemical systems.
A paper describing the research appears in the journal Nature on September 3. Kevin Cherry, Ph.D., is the study’s first author.
A robot learns to handle bulky objects like humans do after just one lesson
For all their technological brilliance, from navigating distant planets to performing complex surgery, robots still struggle with a few basic human tasks. One of the most significant challenges is dexterity, which refers to the ability to grasp, hold and manipulate objects. Until now, that is. Scientists from the Toyota Research Institute in Massachusetts have trained a robot to use its entire body to handle large objects, much like humans do.
Tesla’s Robotaxi Strategy EXPLAINED
Questions to inspire discussion.
Business Strategy and Market Impact.
💼 Q: How is Tesla positioning its robo taxi service in the market? A: Tesla is aiming to change the world towards sustainable transport, winning the first two-month race in deployment, service area, and metrics, rather than engaging in an “online dork battle” about robo taxis.
📊 Q: What’s Tesla’s approach to incidents in its robo taxi service? A: Tesla is carefully managing the launch to minimize the impact of incidents on reaching peak gross margin and revenue, prioritizing this over the cost of safety monitors.
FSD Supervised in Australia.
🦘 Q: How successful is Tesla’s FSD Supervised rollout in Australia? A: It’s considered a success story, with 8 cameras processing live information, navigating complex environments like Brisbane’s “spaghetti bowl” of ramps and exits, and handling roundabouts and highway merges.
Shadow AI Discovery: A Critical Part of Enterprise AI Governance
MITs State of AI in Business report revealed that while 40% of organizations have purchased enterprise LLM subscriptions, over 90% of employees are actively using AI tools in their daily work. Similarly, research from Harmonic Security found that 45.4% of sensitive AI interactions are coming from personal email accounts, where employees are bypassing corporate controls entirely.
This has, understandably, led to plenty of concerns around a growing “Shadow AI Economy”. But what does that mean and how can security and AI governance teams overcome these challenges?