Amazon Prime Day is live. See the best deals HERE. Air quality can make a huge difference in your home's comfort level. We may earn revenue from the products available on this page and participate in affiliate programs. Unfortunately, dust, pet hair, pollen, and a ton of other airborne nonsense wants to get in the way of our good times.

Data-driven autonomous driving motion generation tasks are frequently impacted by the limitations of dataset size and the domain gap between datasets, which precludes their extensive application in real-world scenarios. To address this issue, we introduce SMART, a novel autonomous driving motion generation paradigm that models vectorized map and agent trajectory data into discrete sequence tokens. These tokens are then processed through a decoder-only transformer architecture to train for the next token prediction task across spatial-temporal series. This GPT-style method allows the model to learn the motion distribution in real driving scenarios. SMART achieves state-of-the-art performance across most of the metrics on the generative Sim Agents challenge, ranking 1st on the leaderboards of Waymo Open Motion Dataset (WOMD), demonstrating remarkable inference speed.

Allow me for a moment to discuss a new poem that has the potential to be a classic: "An Ode to the Infield Fly Rule." An esoteric baseball regulation, the infield fly rule is designed to prevent infielders from dropping pop flies intentionally to enable cheap double plays. I suspect that this might be the first poem ever written on this important topic. "Oh Infield Fly Rule, thou art a treasure A beacon of fair play beyond measure We thank thee for thy guidance and thy grace In the great game of baseball, thou dost hold a special place."

A Data Science Technology Company helping enterprises harness their data and build AI-driven innovative solutions. Are you sure you want to view these Tweets? This #MachineLearning use case provides an in-depth analysis of a Transit system in San Francisco Bay Area. These insights will help the organization to smoothly plan and evaluate its services. If your #ATMs are down, what are the chances of your customers switching to your competitors?

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Two artificial intelligence companies are working on a pair of technology-imbued spectacles designed to track the severity of Parkinson's symptoms. UK start-up Emteq and Munich-based audEERING, both of which specialise in technology designed to track emotional responses, will collaborate on a device that will use facial tracking and vocal analysis to track "key physical indicators" of Parkinson's disease. Emteq designs sensor-laden wearable devices capable of tracking facial expression, which are interpreted by the company's AI platform to gauge emotional responses. AudEERING, meanwhile, is an audio analysis firm that uses machine intelligence and deep learning techniques to determine the emotional state of the speaker. The'smart' glasses will combine Emteq's hardware and emotion-tracking technology with an AI model developed by audEERING said to be capable of detecting vocal changes associated with Parkinson's Disease.