Naira_Nicol's comments

Academic authors are shocked and concerned after discovering that Taylor & Francis, a major academic publisher, sold access to their research to Microsoft for use in developing AI systems. The deal, worth about £8 million ($10 million) in its first year, was revealed in a trading update by Taylor & Francis' parent company, Informa, in May 2024.

Many authors were unaware of this arrangement, as Taylor & Francis did not notify them or provide an option to opt out. Additionally, there is no indication that authors will receive any extra compensation for the use of their research by Microsoft. This lack of communication and the inability to opt out have raised significant concerns among the academic community about transparency and author rights.

Dr. Ruth Alison Clemens, a lecturer in modern English literature, voiced her frustration, stating that she only learned about the deal through word of mouth and was dismayed that Taylor & Francis did not publicize the information more widely. The Society of Authors has also criticized the publisher for not consulting with authors before finalizing the deal and highlighted potential issues related to copyright, moral rights, and data protection.

Taylor & Francis has defended the arrangement, claiming that it protects the integrity of the authors' work and limits the verbatim reproduction of text. However, the academic community remains wary, with many calling for clearer policies and better communication regarding such partnerships in the future.

Game Designers are making our Life Colorful and Stressfull...

Yes, ONNX Runtime with WebGPU for removing backgrounds in web browsers is a required step forward in web-based image processing. It's a fast engine for running machine learning models trained with ONNX. And because WebGPU is designed for web-based graphics and compute tasks, its functionality is similar to that of native GPU programming.

It's handel the complex image processing tasks like background removal to happen quickly and in real-time. This approach can deliver up to a 20x speed boost compared to traditional CPU methods. It attracts user interactions for sure.

Developers convert machine learning models trained in tasks like semantic segmentation to ONNX format using ONNX. These models run efficiently in browsers with ONNX Runtime and accelerated WebGPU computations. This integration democratizes access to advanced image processing capabilities that were previously limited to native apps, and now they're available with standard web technologies.

What is that?

What's the meaning of that?

Comments about AI often sound negative because people are worried about what it might mean for the future. They might not understand it well, or they've seen scary stuff about AI in movies. Plus, there are real concerns about things like privacy and fairness.

Fear of the unknown Misinformation Lack of understanding Ethical concerns

Yes, mobile computers can still be powered by AA batteries, Like it's less common in modern devices due to rechargeable battery and the long mobile battery life. there are still portable devices, like handheld gaming consoles, portable radios, and other types of computers.

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Contemporary AI systems are now becoming human-competitive at general tasks,[3] and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us? Should we risk loss of control of our civilization? Such decisions must not be delegated to unelected tech leaders. Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. This confidence must be well justified and increase with the magnitude of a system's potential effects. OpenAI's recent statement regarding artificial general intelligence, states that "At some point, it may be important to get independent review before starting to train future systems, and for the most advanced efforts to agree to limit the rate of growth of compute used for creating new models." We agree. That point is now.

Will try