10 “Best” AI Transcription Software & Services (April 2024)
I Tried These AI-Based Productivity Tools. Here's What Happened
I've used only one image that I created with Midjourney, for a blog post. It was a fun process, but the image itself is low quality and has random elements that make no sense. With Midjourney, you get four square images as output and can ask to regenerate different versions of each of them. I got frustrated thinking that I couldn't make a small change to an image I otherwise liked, or that Midjourney seemed to generate only square images, which is not what I needed for blog posts.
I found out later that adding image dimensions to the prompt creates nonsquare images, and when doing research for this article I learned that Midjourney released Inpainting at the end of August 2023, allowing you to select parts of the image and edit them separately. This is what happens when non-techy people use tech; I can't fault AI for that.
The most controversial subscription I'm happy to pay for is ChatGPT+, for $20 a month. ChatGPT recently crossed the 100 million active user mark, and has completely transformed the AI landscape. I'm surprised how many writers publicly deride ChatGPT, while almost every writer I know uses it—just not for writing.
By definition, you can't use ChatGPT for truly creative work, because its output is "based on existing data and programmed algorithms." It can only summarize, distill, copy, and paste. I use it to learn the basics about concepts, devices, time periods, or events that I write about, and use that basic explanation as a starting point for research. I use ChatGPT to find synonyms and alternatives to whole phrases. I can narrow down research studies and articles quickly because I can search with highly specific prompts rather than simple keywords or terms. Unfortunately, ChatGPT's knowledge data isn't up-to-date, so it won't find the most recent studies. I love it for brainstorming titles, and chapter and section headings. It's also great for checking title case and correct citation formatting. In other words, ChatGPT is my one-stop assistant instead of toggling between Google, my thesaurus, research database, and CMOS formatting tool.
As a ghostwriter, I regularly record interviews with authors to collect book content, so I started using Otter.Ai to transcribe these calls. The transcripts are generally good, but the tech is glitchy, keeps signing in and out, and transcribes only up to 90 minutes at a time, even with a paid version. Worse, Otter joins your meetings even if you don't. This is the default setting, and even when you disable it, the function still sometimes glitches and leads to the Otter assistant showing up uninvited. The default setting also allows the platform to email everyone in the meeting the transcript and invite them to start a free trial, which has weirded out some of my clients. I'm still looking for the perfect automated tool that records video and audio separately and provides a transcript without being creepy AF.
My initial FOMO ended up costing me quite a bit of time and money, but gave me some clarity, too. Turns out that while I'd like to sit at the cool table, I do care more about looking like me than looking poreless. I trust my own voice over ChatGPT's edits, and you should too. Not everything has to be captured, as the CEO of Otter argues. In fact, it's the ephemeral nature of undocumented moments that makes me feel most alive. But that doesn't mean I'll get tired of learning about the newest AI tool promising the closest thing to magic I've ever seen.
So, here's my super official ranking of all the tools I've used so far:
After I put the vacation snapshot back up as my profile picture, I called the friend who always has an eye for my best angles while capturing my most recognizable facial expressions.
Turns out, yes, she's for hire as a photographer.
Apple Finally Pulls Generative AI Nude Apps From The App Store
App Store icon
Apple has removed apps from the App Store that claimed to make nonconsensual nude imagery, a move that demonstrates Apple is now more willing to tackle the hazardous app category.
The capabilities of generative AI to create images based on prompts has become a very useful tool in photography and design. However, the technology also has been misused in the creation of deep fakes — and nonconsensual pornography.
Despite the danger, Apple has been remarkably hands-off from the problem. Prior to the recent move, it hadn't done much to fix a potentially major problem.
In a report by 404 Media, Apple was informed of a number of AI image generation apps available in the App Store. Specifically, they were apps that were marketed as able to create nonconsensual nude images.
The apps offered features such as face-swaps on adult images. Others were marketed as "Undress" apps, virtually stripping the clothing off of subjects of otherwise innocuous photos.
After being alerted to the apps and related advertising, Apple removed three of them from the App Store. Google similarly removed apps from the Play Store.
The report's investigation previously raised the issue that Instagram advertises the apps through Meta's Ad Library, Once the ads were flagged, Meta deleted them.
Apple's removal of the apps from the App Store is good news, but with some lingering issues. For a start, Apple didn't manage to ban the apps as part of its App Store Review process, but instead had to be alerted by third parties to their existence.
Even so, it is a step up from previous attempts by the publication to combat the apps.
Reports in 2022 about the apps explained that they initially appeared innocent on the App Store pages. However, the deep fake porn capabilities were advertised on porn sites.
At the time, Apple and Google were alerted to them, but declined to remove the apps. Instead, the companies were told to stop running the ads on the adult sites, and the apps were allowed to persist in the App Store
Despite the order, one of the apps continued marketing its adult features until 2024, when it was pulled from the Google Play Store.
Apple's decision to finally remove the offending apps from the App Store is the latest move Apple made to try and keep its AI dealings as above board as possible.
As well as using training methods for AI language models that preserve privacy, Apple has also avoided using copyrighted works in an illegal way. While Microsoft and OpenAI have been sued by the New York Times for copyright infringement from using its articles for AI training, Apple has instead tried to license works from major publishers in exchange for millions of dollars.
Apple's IPhone AI Plans Confirmed With New Software Upgrade
Apple Phone 15 Pro on sale (Photographer: Dhiraj Singh/Bloomberg)
© 2023 Bloomberg Finance LPUpdated April 27: article originally posted April 25.
How Apple will improve the next iPhone 16 and iPhone 16 Pro with artificial intelligence is one of 2024's big questions. Now we know more about Apple's plans to use AI in the iPhone, its approach and how it will sell it to consumers.
Apple has submitted eight large language models to the Hugging Face hub, an online resource for open-source AI implementations. LLMs are datasets that generative AI applications use to process the inputs and work through as many iterations as necessary to arrive at a suitable solution.
The larger the LLM, the more data is available, and it should not be surprising that those data sets were originally built in the cloud to be accessed as an online service. There has been a push to create LLMs with a small enough data footprint to run on a mobile device.
This requires new software techniques, but it will also place a demand on the hardware to allow for more efficient processing. Android-focused chipset manufacturers such as Qualcomm, Samsung and MediaTek offer system-on-chip packages optimized for generative AI. Apple is expected do the same with the next generation of Axx chips to allow more AI routines to take place on this year's iPhone 16 family rather than in the cloud.
Running on the device means user data would not need to be uploaded and copied away from the device to be processed. As the public becomes more aware of the concerns around AI privacy, this will become a key marketing point.
Microsoft store is seen In Manhattan, New York (Photo by Beata Zawrzel/NurPhoto via Getty Images)
NurPhoto via Getty ImagesUpdate: Saturday, April 27: Apple is not the only company hard at work on smaller scale yet effective language models for mobile devices. This weekend, Microsoft has published details and developer guides for Phi-3. The smallest of these three generative AI models, Phi-3 Mini, is available through Microsoft's Azure AI Studios, Ollama and Hugging Face. Phi-3 Small and Phi-3 Medium are still in their developmental phase.
Phi-3 is a large language model that works within a small footprint. Microsoft claims it can outperform models twice its size "on key benchmarks" and draws a direct and favourable comparison to GPT-3.5T. Crucially, Phi-3 Mini will comfortably run on Apple's A16 bionic chip, which means third-party developers can target the iPhone 14 Pro and 14 Pro Max as well as the iPhone 15 family and any future models.
2024 will see the launch of many LLMs, from hobbyists right through to the majors of Silicon Valley (and Redmond). Some will be licensed by their developers out to hardware manufacturers; there is a realistic chance that Apple will work with AI models from Google and Microsoft for iOS 18 and the upcoming iPhones.
The models are easily available to third-party developers. They will have a wide choice of AI tools and will be looking for cross-platform support to ease the development process. As manufacturers lean into AI for marketing and differentiation, the apps that users crave can join the AI revolution without being locked into a single choice made by the manufacturer.
The Apple retail store in Grand Central Terminal (Photo by Drew Angerer/Getty Images)
Getty ImagesAlongside the code of these open-source efficient language models, Apple has published a research paper (PDF Link) on the techniques used and the rationale behind the choices, including the decision to open-source all of the training data, evaluation metrics, checkpoints and training configurations.
This follows the release of another LLM research paper by Cornell University, working alongside Apple's research and development team. This paper described Ferret-UI, an LLM that would help understand a device's user interface and what is happening on screen and offer numerous interactions. Examples include using voice to navigate to a well-hidden setting or describing what is shown on the display for those with impaired vision.
Three weeks after Apple released the iPhone 15 family in 2023, Google launched the Pixel 8 and Pixel 8 Pro. Proclaiming them as the first smartphones with AI built-in, the handsets signaled a rush to use and promote the benefits of generative AI in mobile devices. Apple has been on the back foot, at least publicly, ever since.
The steady release of research papers on new techniques has kept Apple's AI plans visible to the industry if not yet to consumers. By providing the open-source code for these efficient language models and emphasizing on-device processing, Apple is quietly signaling how it hopes to stand out against the raft of Android-powered AI devices, even as it talks to Google about licensing Gemini to power some of the iPhone's AI features.
Now take a closer look at the leaked design of the iPhone 16 and iPhone 16 Pro...
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