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Engineers enlist NASA to send yet another time capsule to the moon — 24 sapphire discs will contain ‘the very essence of humanity’ printed over 170 billion pixels but who will read them?

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NASA, in collaboration with a team of international scientists, researchers, designers, and artists led by French engineer Benoit Faiveley, is set to send another time capsule to the moon. 

The project, titled “Sanctuary on the Moon”, is part of NASA’s ambitious Artemis CLPS program and enjoys the support of UNESCO and the patronage of French President Emmanuel Macron.

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Apple Podcasts transcripts: How to find and read them in iOS 17.4

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It just became a lot easier to read along with a podcast, or pull an interesting quote out of one. The Apple Podcasts app now automatically generates transcripts for series and episodes.

Here’s how to find and read these transcripts in the iPhone Podcasts app.

Every episode on Apple Podcasts will get a transcript

Podcasts have proliferated since 2004 and become a popular medium for sharing everything from news reports on current world events to jokes and cooking tips. Those with hearing loss can’t take advantage of them, however. But a transcript solves that problem. And rather than expect every podcaster to make a written version of their program, Apple took on the job.

“Apple introduces transcripts for Apple Podcasts, an innovative new feature that makes podcasts more accessible and easier to navigate,” the company promised.

Beyond just reading the full text of all episodes, the new feature enables users to search episodes for specific words or phrases. And when they find one, they can tap the text to play from that point in the episode.

How to read transcripts for Apple Podcasts on iPhone

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The feature is part of iOS 17.4, which launched Tuesday. So the first step in making use of this feature is to install the latest version of iOS.

Next, open the Apple Podcasts app (duh) and go to a podcast. Look in the lower left-hand corner for an icon that looks like a speech bubble with a quotes symbol inside. Tap on it.

This opens Apple’s automatically generated podcast transcript. And it opens exactly where you are in the podcast, with the current sentence highlighted.

The highlighting follows along in the transcript as you listen to the podcast. Or you can tap on a section of the transcript to jump to that portion of the audio, as previously noted.

Use your finger to drag the text upward and it’ll expand to fill the screen. A Search button also appears.

The audio controls stay on the screen when the text first appears, but if you scroll down they’ll disappear. Scroll up to bring the controls back. Or just wait a bit — they come back on their own.

Tap the icon in the lower left-hand corner of the screen again to close the transcript.

Computer-generated podcast transcripts

Transcripts are automatically generated after a podcast is published. Apple warns there will be “a short delay while we process your transcript.”

And these won’t be only for new episodes. Apple says podcast transcripts for back-catalog episodes are being added over time.

The text versions are created with voice-recognition software, but in my experience are quite accurate. That said, mumbled words or ones covered with background noise get left out.

Happily, the feature is available in a range of languages beyond English. Also available are French, German and Spanish. But this isn’t a translation service — you only get a Spanish-language transcript for a podcast that’s in Spanish, for example. That said, you can copy the text into your favorite translation app if you wish.

Now part of iOS 17.4 and coming to macOS 14.4

The feature is included in iOS 17.4. All iPhone users who install the OS update can read Apple’s new podcast transcripts. The same goes for iPadOS 17.4.

In addition, transcripts for Apple Podcasts will arrive in macOS 14.4 Sonoma. That’s not out yet, but is expected in mid-March.



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New Samsung microSD cards with read speeds up to 800 MB/s

New Samsung microSD cards 800 MBs

Samsung Electronics has just announced the release of two new microSD cards that are set to change the way we think about portable storage. These cards are not only fast but also come with a storage capacity that’s hard to beat, making them perfect for anyone who needs to store and access large amounts of data quickly and efficiently. Whether you’re a professional working with high-resolution videos or someone who enjoys capturing life’s moments in stunning detail, these microSD cards are designed to keep up with your demands.

At the forefront of this new lineup is the 256 GB SD Express microSD card, which boasts an impressive sequential read speed of up to 800 MB/s. This is not just a step up in speed; it’s a leap that brings the performance of a solid-state drive (SSD) into the palm of your hand. Imagine being able to transfer a full-length HD movie in just seconds – that’s the kind of speed we’re talking about. This card is the first of its kind in the industry, setting a new standard for data transfer rates and leaving traditional UHS-1 microSD cards in the dust. It even rivals the performance of some SATA SSDs, giving you quick access to your files and making it an indispensable tool for anyone who needs their data fast and on the move.

For those who need even more space, Samsung has also introduced a 1 TB UHS-1 microSD card. This card takes advantage of Samsung’s latest 8th generation 1-terabit V-NAND technology, allowing you to store an enormous amount of data in a device that’s no larger than your thumbnail. With this card, you can carry around a whole library of 4K videos, high-resolution photos, and large applications without worrying about running out of space.

Portable Storage with Read Speeds up to 800 MB/s

Durability is another standout feature of these new microSD cards. The 1 TB card, for example, is built to withstand water, extreme temperatures, drops, and electromagnetic interference. This means that no matter where you are – be it on a rugged mountain trail or in the hustle and bustle of city life – your data is safe. This is especially important for those who rely on their digital content to be available and intact at all times.

The SD Express card also comes with a special feature called Dynamic Thermal Guard technology. This system actively monitors and manages the card’s temperature to ensure stable performance. This is particularly important for tasks that require a lot of processing power, such as running complex AI algorithms or recording high-definition video. By preventing overheating, this technology helps maintain the card’s efficiency and reliability.

The 256 GB SD Express card is set to hit the market later this year, and the 1 TB UHS-1 card is expected to be released in the third quarter. These cards are highly anticipated by tech enthusiasts and professionals alike, who are looking to push the boundaries of what’s possible with their devices.

Samsung microSD cards 2024

Samsung’s latest microSD cards are poised to elevate the standards of portable storage. With their SSD-like speeds, massive storage capacity, and comprehensive durability and thermal management features, these cards are ready to enhance your mobile computing and on-device AI applications. Keep an eye out for their release, and get ready to experience a new level of digital convenience and performance.

Samsung Electronics has unveiled two groundbreaking microSD cards that redefine the capabilities of portable storage. These cards are not just fast; they offer a level of storage capacity that is exceptional, catering to the needs of professionals and enthusiasts who require quick and expansive data storage solutions. For those dealing with high-resolution videos, these microSD cards promise to keep pace with the high demands of their work, ensuring that large files can be stored and accessed with ease.

Expansive Storage with Cutting-Edge Technology

The new 256 GB SD Express microSD card is a game-changer, offering a sequential read speed of up to 800 MB/s. This remarkable speed is akin to that of a solid-state drive (SSD), fitting this advanced technology into a compact form. The ability to transfer large files such as HD movies in mere seconds exemplifies the card’s superior data transfer rates. This innovation is not just a minor improvement but a significant leap forward, surpassing traditional UHS-1 microSD cards and even rivaling some SATA SSDs in performance.

For users who require even more storage, Samsung has introduced a 1 TB UHS-1 microSD card. This card utilizes Samsung’s advanced 8th generation 1-terabit V-NAND technology, enabling it to store a vast amount of data in a minuscule package. Users can now carry a comprehensive collection of 4K videos, high-resolution images, and extensive applications without the fear of running out of space, making it an ideal solution for content creators and data-heavy users.

The durability of these microSD cards is another significant aspect. The 1 TB card is engineered to be resilient against water, extreme temperatures, drops, and electromagnetic interference. This robust construction ensures that your data remains secure and accessible in various environments, whether you’re navigating through challenging outdoor conditions or the urban jungle.

Enhanced Performance with Thermal Management

The SD Express card is equipped with a unique feature known as Dynamic Thermal Guard technology. This innovative system actively monitors the card’s temperature, adjusting it to maintain stable performance. This feature is crucial for intensive tasks that generate significant heat, such as executing complex AI algorithms or capturing high-definition video. By mitigating the risk of overheating, the technology preserves the card’s efficiency and long-term reliability.

The 256 GB SD Express card is scheduled for release later in the year, while the 1 TB UHS-1 card is expected to become available in the third quarter. These cards are eagerly awaited by technology enthusiasts and professionals who are eager to expand the capabilities of their devices.

Samsung’s latest microSD cards are set to transform the landscape of portable storage. With their SSD-like speeds, substantial storage capacities, and robust durability and thermal management features, these cards are prepared to enhance mobile computing and on-device AI applications. As the release dates approach, users can look forward to a new era of digital efficiency and performance.

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How to use ChatGPT Vision to read & understand images in automations

How to use ChatGPT Vision to read and understand images in Zapier automations

Have you ever wanted to create an automation capable of reading and understanding images and ultimately taking actions upon what it sees to help improve your productivity or business workflow? Perhaps upload a photo to your Google Drive, a system instantly kicks into gear, analyzing every detail of that image and setting off a chain of actions based on what it finds. This isn’t a glimpse into a distant future; it’s a reality you can create today using OpenAI’s ChatGPT Vision image analysis technology and Zapier’s automation platform. This guide will show you how to combine these powerful tools to streamline your workflow and make your digital life infinitely more efficient.

Thanks to the launch of ChatGPT Vision you can now create AI automations that can read and understanding images and deciding autonomously. To begin, you’ll need to get familiar with OpenAI’s API, which is a sophisticated tool that can dissect the contents of an image, spot patterns, and generate useful metadata. To harness this power, you’ll integrate the OpenAI API with Zapier. Start by securing an OpenAI account and obtaining your API key. Then, you’ll create a new “Zap,” which is what Zapier calls an automated workflow. This Zap will connect your Google Drive to OpenAI, setting the stage for the magic to happen.

Creating automations with ChatGPT Vision

The next step is to set up a trigger in Zapier. This trigger prompts the system to spring into action whenever you upload a new image to a specific Google Drive folder. To do this, you’ll select Google Drive as the trigger app and choose the “New File in Folder” option. You’ll need to pinpoint the exact folder you want to monitor and make sure Zapier has the permissions to access it.

Other articles we have written that you may find of interest on the subject of  OpenAI’s new AI vision model  which is available in ChatGPT  and through its API system :

Once your trigger is in place, you’ll need to configure the action that calls upon OpenAI’s API. When the conditions for your trigger are met—meaning a new image has been uploaded—Zapier will send a request to the API. This request will include your API key and a data payload that contains the image URL from Google Drive, all formatted according to OpenAI’s specifications.

Supported image formats

It’s important to note that OpenAI’s API can work with several image formats, including PNG, JPEG, GIF, and WEBP. You’ll want to ensure that the images you’re uploading to Google Drive are in one of these formats. If they’re not, you’ll have to convert them before they can be analyzed. For OpenAI’s API to examine your images, the URLs must be properly structured. They need to be accessible to the API, which might mean changing the sharing settings in Google Drive to allow access. Additionally, the URLs must be encoded in a way that the API can recognize.

Permissions are key in this automation process. You’ll need to adjust your Google Drive sharing options to enable OpenAI’s API to retrieve and analyze the images. This might involve setting the images to “public” or sharing them with a service account that’s connected to the API. If you find that your images are not in a compatible format, you’ll need to convert them. This can be done manually, or you can set up an automated process within Zapier, which can use other apps or its own tools to get the images ready for OpenAI’s API.

Automating the process with Zapier

Testing your setup is an essential step. You should upload various images to your designated Google Drive folder and observe the Zap in action. This will trigger the analysis process. Pay close attention to the output from OpenAI’s API to ensure that the system is working as expected and that the analysis meets your needs. Maintaining the quality of your API-driven automation is crucial. You should regularly test your Zaps and keep an eye on the performance of the OpenAI API to ensure that the image analysis remains accurate and reliable. Be aware of any updates to the API or changes in the supported formats, and adjust your automation as needed.

By following this guide, you can create an advanced system that leverages the strengths of Google Drive’s image management, OpenAI’s analytical capabilities, and Zapier’s automation efficiency. Whether you’re using it for work or personal projects, automating image analysis with OpenAI through Zapier can free up your time and provide valuable insights. This allows you to focus on more strategic tasks and creative endeavors. With this setup, you’re not just optimizing your workflow; you’re unlocking a new level of productivity and insight that can transform the way you handle digital images.

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How to read and process PDFs locally using Mistral AI

How to read and process PDFs locally using Mistral AI model

If you would prefer to keep your PDF documents, receipts or personal information out of the hands of third-party companies such as OpenAI, Microsoft, Google and others. You will be pleased to know that you curb process and read PDFs on your own computer or personal or private network using the Mistral AI model.

Over the last 18 months or so artificial intelligence (AI) has seen significant advancements, particularly in the realm of document processing, thanks to large language models being able to read. One such advancement is the use of AI to read and process PDF documents locally. This guide will provide more details on how you can keep your PDF documents safe and secure by processing them on your own computer or local network. Using Katana ML’s open source library to process PDF documents locally with the Mistral AI model.

“Mistral-7B-v0.1 is a small, yet powerful model adaptable to many use-cases. Mistral 7B is better than Llama 2 13B on all benchmarks, has natural coding abilities, and 8k sequence length. It’s released under Apache 2.0 licence, and we made it easy to deploy on any cloud.”

Katana ML is an open source MLOps infrastructure that can be used in the cloud or on-premise. It offers state-of-the-art machine learning APIs that cater to a wide array of use-cases. One such application is the processing of PDF documents using the Mistral 7B model. This model, despite being small in size, boasts impressive performance metrics and adaptability.

How to read and process PDFs locally using Mistral AI

Other articles we have written that you may find of interest on the subject of Mistral AI :

Mistral 7B is a 7.3 billion parameter model that outperforms its counterparts, Llama 2 13B and Llama 1 34B, on various benchmarks. It even approaches CodeLlama 7B performance on code while maintaining proficiency in English tasks. The model uses Grouped-query attention (GQA) for faster inference and Sliding Window Attention (SWA) to handle longer sequences at a smaller cost. The model is released under the Apache 2.0 license and can be used without restrictions.

The process of using this model to read and process PDFs locally can be executed on platforms like Google Colab or a local machine. The choice between these two depends on the user’s preference and needs. Google Colab offers the advantage of cloud-based processing, eliminating the need for high-end hardware. However, it also comes with limitations, such as a restricted amount of free GPU usage. On the other hand, using a local machine allows for greater control and customization. However, the processing speed might be slower due to hardware limitations.

How to read and process PDFs locally using Mistral AI

To illustrate the process, let’s consider a PDF invoice example. The first step involves cloning the repository from Katana ML and installing the necessary requirements. The user then downloads a quantized model based on the system’s RAM capacity. The configuration file is then edited to optimize speed and quality. The data from the PDF is converted into embeddings and stored in Vector DB, a process known as data injection. The main.py file is then run to ask questions and get answers based on the processed data.

Despite its impressive capabilities, the Mistral AI model is not without its limitations. The processing speed can be slow due to the limitations of current technology. Furthermore, like any AI model, Mistral 7B is not immune to “hallucinations” or mistakes. These are instances where the AI generates incorrect or nonsensical responses.

However, the potential applications of this technology are vast. For example, it can be used to extract structured information from unstructured documents, like invoices or contracts. This can significantly streamline processes in industries like finance, law, and administration.

Looking forward, there are several possibilities for optimization and improvements. For instance, further fine-tuning of the model could enhance its performance. Additionally, advancements in hardware technology could significantly speed up the processing time.

Using Katana ML’s open source library to process PDF documents locally with the Mistral AI model is a promising application of AI technology. Despite its current limitations, it offers a glimpse into the future of document processing and the potential of AI in transforming mundane tasks into automated processes.

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