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Category: robotics/AI – Page 308

A portable sweeping frequency reader was kept nearby to record and analyze the signals from the RF tags (it serves as the machine part of HMI).

The researchers demonstrated that their smart contact lenses can detect gazing directions and real-time gazing points, which could be used for robot control and software interaction.

Further, they showed that the lenses are very stable and can be worn for up to 12 hours in different environmental conditions. They have also shown that the lenses can detect eye closure.

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According to a statement by the firm, the study showed that AI models trained on hand images achieve comparable accuracy to those using facial images, with an average error of 4.1 and 4.7 years in predicting chronological age.

The AI model in the study was primarily trained by employing the Indian population dataset to ensure representation of diverse skin tones and address AI’s bias challenges, especially pertaining to ethnicity-specific considerations in age prediction.

By focusing on the Indian population, the study aimed to develop an AI model tailored to this demographic, mitigating biases and promoting fairer AI solutions. Additionally, the research’s market relevance in India’s growing skincare and AI sectors underscores the strategic importance of using an Indian dataset for this study.

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Chapters 00:00 — Intro + Background 05:06 — From KART to KAN 07:56 — MLP vs KAN 16:05 — Accuracy: Scaling of KANs 26:35 — Interpretability: KAN for Science 38:04 — Q+A Break 57:15 — Strengths and Weaknesses 59:28 — Philosophy 1:08:45 — Anecdotes Behind the Scenes…

Portal is the home of the AI for drug discovery community. Join for more details on this talk and to connect with the speakers: https://portal.valencelabs.com/logg.

Abstract: Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes (\.

Continue reading “KAN: Kolmogorov-Arnold Networks | Ziming Liu” | >

(TNS) — The global race for computational power is well underway, fueled by a worldwide boom in artificial intelligence. OpenAI’s Sam Altman is seeking to raise as much as $7 trillion for a chipmaking venture. Tech giants like Microsoft and Amazon are building AI chips of their own. The need for more computing horsepower to train and use AI models—fueling a quest for everything from cutting-edge chips to giant data sets—isn’t just a current source of geopolitical leverage (as with US curbs on chip exports to China). It is also shaping the way nations will grow and compete in the future, with governments from India to the UK developing national strategies and stockpiling Nvidia graphics processing units.

I believe it’s high time for America to have its own national compute strategy: an Apollo program for the age of AI.

In January, under President Biden’s executive order on AI, the National Science Foundation launched a pilot program for the National AI Research Resource (NAIRR), envisioned as a “shared research infrastructure” to provide AI computing power, access to open government and nongovernment data sets, and training resources to students and AI researchers.

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Editor’s note: This story is being highlighted in ASU Now’s year in review. Read more top stories from 2018 here.

In a major advancement in nanomedicine, Arizona State University scientists, in collaboration with researchers from the National Center for Nanoscience and Technology (NCNST) of the Chinese Academy of Sciences, have successfully programmed nanorobots to shrink tumors by cutting off their blood supply.

“We have developed the first fully autonomous, DNA robotic system for a very precise drug design and targeted cancer therapy,” said Hao Yan, director of the ASU Biodesign Institute’s Center for Molecular Design and Biomimetics and the Milton Glick Professor in the School of Molecular Sciences.

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ChatGPT is about to become a lot more useful.

OpenAI on Monday announced its latest artificial intelligence large language model that it says will make ChatGPT smarter and easier to use.

The new model, called GPT-4o, is an update from the company’s previous GPT-4 model, which launched just over a year ago. The model will be available to unpaid customers, meaning anyone will have access to OpenAI’s most advanced technology through ChatGPT.

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