Apple offers more ways to order the all-new iPhone 15 and Apple Watch lineups

https://www.apple.com/newsroom/2023/09/apple-offers-more-ways-to-order-the-all-new-iphone-15-and-apple-watch-lineups/

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2. Adobe unveils powerful new AI and 3D features

Sometimes you need a little help to improve the overall speech quality in your videos. Whether it’s due to scenarios like a poorly placed mic, excessive background noise or, low-quality archive footage or any other reason, poor audio can be very difficult to clean up. Enhance Speech uses AI to magically remove background noise and improve the quality of poorly recorded dialogue, making it sound as if it was recorded in a professional studio. You can also use the mix slider to incorporate some of the background noise to make it sound just right.

Text-Based Editing improvements

more: https://blog.adobe.com/en/publish/2023/09/13/new-ai-3d-features-at-ibc-2023

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Всякий раз, когда вы захотите создать фотореалистичные изображения в Midjourney, вам придется писать подсказки определенным образом.

Давайте начнём с Фотореализма (Photorealism)

Детализация: обратите внимание на мельчайшие детали. Суть фотореализма заключается в том, чтобы запечатлеть объект таким, какой он есть, в его наиболее подробной форме.

Освещение: используйте освещение в своих интересах. Это может помочь выявить текстуры и детали объекта.

Перспектива: используйте перспективу, чтобы объект выглядел реальным. Небольшое изменение перспективы может иметь большое значение.

Резкость: изображение должно быть резким и ясным. Любая размытость может испортить фотореалистичный эффект.

Постобработка. Используйте постобработку, чтобы улучшить детализацию и резкость изображения.

Лучше использовать английский язык для описания ваших пожеланий для генерации изображений.

1. A stunning and intimate portrait of a ballet dancer mid-performance, captured with a Canon EOS R6 mirrorless camera and a Canon RF 85mm f/1.2L USM lens. —ar 3:2
2. A dynamic and engaging short film showcasing a talented street artist at work, filmed with a Sony FX9 full-frame cinema camera and edited in Adobe Premiere Pro for maximum impact. —ar 16:9
3. A breathtaking aerial shot of a lush, verdant forest, captured with a DJI Phantom 4 Pro drone and edited in Adobe Lightroom for maximum impact. —ar 16:9
4. A dramatic and powerful black and white portrait of a musician mid-performance, expertly captured with a Nikon D850 DSLR camera and a Nikkor 85mm f/1.8G lens. —ar 3:2
5. A striking and intense portrait of a professional boxer mid-match, captured with a Canon EOS-1D X Mark III DSLR camera and a Canon EF 70-200mm f/2.8L IS III USM lens. —ar 3:2

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01. Teaching with AI: https://openai.com/blog/teaching-with-ai

We’re releasing a guide for teachers using ChatGPT in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias.
How teachers are using ChatGPT

• Role playing challenging conversations
• Building quizzes, tests, and lesson plans from curriculum materials
• Reducing friction for non-English speakers
• Teaching students about critical thinking

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02. Google Gemini Eats The World – Gemini Smashes GPT-4 By 5X, The GPU-Poors:

https://www.semianalysis.com/p/google-gemini-eats-the-world-gemini

Before Covid, Google released the MEENA model, which for a short period of time, was the best large language model in the world.
GPUs vs TPUs fight.. hmm.. interesting

GPUs and TPUs are both types of hardware accelerators used to speed up machine learning workloads, but there are some key differences between the two:

Architecture: GPUs have a more generalized architecture that can be used for a variety of computational tasks, including machine learning. TPUs, on the other hand, are specifically designed for deep learning, which can lead to better performance for some neural network workloads.

Memory: GPUs typically have larger memory capacities than TPUs, which can be beneficial for certain types of workloads that require large amounts of memory.

Precision: TPUs are designed to perform computations at lower precision than GPUs, which can reduce memory requirements and improve performance for some deep learning workloads.

Price: TPUs are generally more expensive than GPUs, both in terms of the hardware itself and the cloud instances that run them. This can make them less accessible to small-scale machine learning projects or individual developers.

GPUs have a more generalized architecture that can be used for a range of computational tasks, while TPUs are specialized for deep learning workloads and can offer better performance for these tasks

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