ChatGPT is in the spotlight, but it’s Whisper—OpenAI’s open-source speech-transcription program—that shows us where machine learning is going.

One day in late December, I downloaded a program called Whisper.cpp onto my laptop, hoping to use it to transcribe an interview I’d done. I fed it an audio file and, every few seconds, it produced one or two lines of eerily accurate transcript, writing down exactly what had been said with a precision I’d never seen before. As the lines piled up, I could feel my computer getting hotter. This was one of the few times in recent memory that my laptop had actually computed something complicated—mostly I just use it to browse the Web, watch TV, and write. Now it was running cutting-edge A.I.

Despite being one of the more sophisticated programs ever to run on my laptop, Whisper.cpp is also one of the simplest. If you showed its source code to A.I. researchers from the early days of speech recognition, they might laugh in disbelief, or cry—it would be like revealing to a nuclear physicist that the process for achieving cold fusion can be written on a napkin. Whisper.cpp is intelligence distilled. It’s rare for modern software in that it has virtually no dependencies—in other words, it works without the help of other programs. Instead, it is ten thousand lines of stand-alone code, most of which does little more than fairly complicated arithmetic. It was written in five days by Georgi Gerganov, a Bulgarian programmer who, by his own admission, knows next to nothing about speech recognition. Gerganov adapted it from a program called Whisper, released in September by OpenAI, the same organization behind ChatGPT and dall-e. Whisper transcribes speech in more than ninety languages. In some of them, the software is capable of superhuman performance—that is, it can actually parse what somebody’s saying better than a human can.

What’s so unusual about Whisper is that OpenAI open-sourced it, releasing not just the code but a detailed description of its architecture. They also included the all-important “model weights”: a giant file of numbers specifying the synaptic strength of every connection in the software’s neural network. In so doing, OpenAI made it possible for anyone, including an amateur like Gerganov, to modify the program. Gerganov converted Whisper to C++, a widely supported programming language, to make it easier to download and run on practically any device. This sounds like a logistical detail, but it’s actually the mark of a wider sea change. Until recently, world-beating A.I.s like Whisper were the exclusive province of the big tech firms that developed them. Read More

Apple and Google’s AI turn in a booming market may sound less than human and raise the ire of voiceover actors, but it has cost benefits

For the first few seconds, the narrator of Kristen Ethridge’s new romance audiobook, Shelter from the Storm, sounds like a human being. The voice is light and carefully enunciated, with the slow pacing of any audiobook narrator, as it begins: “There’s a storm coming, and her name is Hope.”

Then, something about the pacing of the words grates on the ear. It’s a little too regular, even robotic. “I know that sounds a little crazy,” the breathy voice continues, grinding out the words. “That something so destructive could be labeled with such a peaceful name.” Read More