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Category: robotics/AI – Page 409

In the digital age, where entertainment is but a click away, a silent yet powerful transformation is underway. Streaming companies, the vanguards of this digital entertainment era, are not just delivering content; they’re crafting experiences, and artificial intelligence (AI) is their most adept tool. Let us explore how AI is not just changing, but revolutionizing the way we consume media.

Gone are the days of aimlessly browsing channels to find something to watch. AI in streaming services is like a discerning director, understanding and curating content to fit the unique tastes of each viewer. It’s an era where your streaming service knows what you want to watch, sometimes even before you do. The great power of AI is personalization, where organizations can create unique user journeys. At the core of AI’s integration into streaming is personalization. Netflix, the colossus of streaming, employs AI algorithms to recommend movies and shows based on your viewing history. However, generally, these recommendation engines based on historical presences have muted value. Traditional metrics leverage past viewing information or collaborative filtering to make content recommendations. However, customer feedback has shown these are imperfect fits in the age of data for precision product-market fit.

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General-purpose humanoid robots using AI are advancing and increasingly gaining investment support to perform tasks that humans do easily.

Humanoid AI smart robots are accelerating with major investments from automotive giants BMW, Honda, Hyundai, Mercedes Benz and Tesla, to name a few. Will this growth and interest accelerate approval of a new 32-hour work week bill earlier?

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The manufacturing process for personalized T-cell therapies hardly begins before it stalls. Why? Right at the start, there is a severe bottleneck: the need to identify patient-derived, tumor-reactive T-cell receptors (TCRs).

To overcome this bottleneck, scientists at the German Cancer Research Center (DKFZ) and the University Medical Center Mannheim have developed predicTCR, a machine learning classifier. According to the scientists, it can identify individual tumor-reactive tumor-infiltrating lymphocyte (TILs) in an antigen-agnostic manner based on single-TIL RNA sequencing.

The scientists also assert that prediTCR can halve the time it takes to get past the bottleneck, helping to reduce the overall time needed to make a personalized T-cell therapy for cancer patients. Since the overall time is at least six months, any reduction in the time needed to complete any manufacturing step is welcome.

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Researchers at the National University of Singapore (NUS) have developed an innovative method for creating carbon-based quantum materials atom by atom. This method combines the use of scanning probe microscopy with advanced deep neural networks. The achievement underlines the capabilities of artificial intelligence (AI) in manipulating materials at the sub-angstrom level, offering significant advantages for basic science and potential future uses.

Open-shell magnetic nanographenes represent a technologically appealing class of new carbon-based quantum materials, which host robust π-spin centers and non-trivial collective quantum magnetism. These properties are crucial for developing high-speed electronic devices at the molecular level and creating quantum bits, the building blocks of quantum computers.

Despite significant advancements in the synthesis of these materials through on-surface synthesis, a type of solid-phase chemical reaction, achieving precise fabrication and tailoring of the properties of these quantum materials at the atomic level has remained a challenge.

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