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Google DeepMind Unveils MusicRL: A Pretrained Autoregressive MusicLM Model of Discrete Audio Tokens Finetuned with Reinforcement Learning to Maximise Sequence-Level Rewards
Google DeepMind’s MusicRL has revolutionized AI music generation. By leveraging human feedback, it shapes music that resonates personally. Its autoregressive model, MusicLM, learns from audience wisdom, a dialogic process employing reinforcement learning. MusicRL outperforms traditional models, offering enchanting, personalized listening experiences. It redefines AI-generated music, enriching the human experience.
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Why Big Tech’s watermarking plans are some welcome good news
Tech companies like Meta, Google, and OpenAI are taking steps to address the spread of AI-generated content. Meta is adding markers to AI-generated images on its platforms, while Google is joining the partnership for a content provenance standard. OpenAI is also implementing new measures for image metadata. However, concerns remain about the effectiveness of these…
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Enhancing Language Model Alignment through Reward Transformation and Multi-Objective Optimization
The study explores aligning language models to desirable attributes, emphasizing improvement of poor outputs and aggregation of rewards learned from human preferences. This transformation technique, combined with logical conjunction, demonstrates substantial improvements in aligning language models to be helpful and harmless using Reinforcement Learning from Human Feedback (RLHF). The findings emphasize effective multi-objective optimization to…
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Unfinished Work Every Sprint? 3 Ways to Break the Habit
A team in California excelled in collaboration and skill but consistently failed to finish their sprint goals due to overcommitting influenced by an unofficial leader, Marc. The pressure to overcommit often stems from leadership or the team itself and can lead to reduced predictability for the organization. Three strategies are recommended to address habitual overcommitting.
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10 Best Midjourney Anthropomorphic Prompts
Midjourney offers anthropomorphic prompts such as anthropomorphic animals like scholar owl, adventurous squirrel, fox thief, barista cat, and pilot dog. Also, prompts for anthropomorphic objects like vintage camera, teacup, car, bull, and lamp are available. With the prompts, one can create various lively and realistic images using Midjourney.
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Apple AI Research Releases MLLM-Guided Image Editing (MGIE) to Enhance Instruction-based Image Editing via Learning to Produce Expressive Instructions
Advanced design tools have revolutionized multimedia and visual design, particularly through instruction-based image editing and the introduction of Multimodal Large Language Models (MLLMs). Researchers from UC Santa Barbara and Apple have developed Multimodal Large Language Model-Guided Picture Editing (MGIE) to enhance image alteration. The study underscores the significance of expressive instructions for improved editing performance.
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This AI Paper Proposes Two Types of Convolution, Pixel Difference Convolution (PDC) and Binary Pixel Difference Convolution (Bi-PDC), to Enhance the Representation Capacity of Convolutional Neural Network CNNs
DCNNs have revolutionized computer vision tasks, but their high energy consumption presents sustainability challenges. Researchers are enhancing DCNN efficiency by introducing PDC and Bi-PDC to capture higher-order local information. These methods improve edge detection and image recognition while maintaining efficiency, as demonstrated through experimental evaluations. Future research aims to optimize the application of these techniques…
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Nvidia CEO Jensen Huang on AI infrastructure, impacts, and investment
Nvidia CEO Jensen Huang advocated for sovereign AI efforts at the World Government Summit in Dubai, emphasizing the need for nations to develop their own infrastructure. He highlighted Nvidia’s success in democratizing AI and discussed plans to produce custom AI chips. Huang also addressed concerns about AI’s impact and investment in AI hardware.
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Google Research Introduces TimesFM: A Single Forecasting Model Pre-Trained on a Large Time-Series Corpus of 100B Real World Time-Points
Google researchers introduced TimesFM, a single forecasting model pre-trained on a large time-series corpus, aiming to improve time series forecasting. The model, based on a patched-decoder style attention mechanism, achieves strong zero-shot forecasting performance and outperforms existing models in efficiency and parameter size, showing promise for reducing training data and computational requirements in this field.…
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Enhanced Audio Generation through Scalable Technology
Technological advancements in audio generation, particularly in high-fidelity synthesis, have led to increased demand for realistic audio experiences. New model EVA-GAN addresses challenges in audio production, leveraging GANs and neural vocoders. With a novel Context Aware Module and Human-In-The-Loop evaluation, EVA-GAN outperforms existing models, significantly improving high-fidelity audio synthesis.