Given an audio waveform, researchers can now produce a virtually identical version that makes speech-recognition software transcribe something else entirely.
Backstory: Adversarial examples have fooled plenty of computer-vision algorithms. While all neural networks are susceptible to such attacks, researchers have had less success with audio. Previous attacks were only able to make subtle tweaks to what the software hears.
What’s new: Berkeley researchers showed that they can take a waveform and add a layer of noise that fools DeepSpeech, a state-of-the-art speech-to-text AI, every time. The technique can make music sound like arbitrary speech to the AI, or obscure voices so they aren’t transcribed.
Brace for annoyance: Imagine playing a music video from YouTube on your speakers and having Alexa “hear” an order for two tons of creamed corn. Welcome to AI attack hell.
Geoffrey Hinton tells us why he’s now scared of the tech he helped build
“I have suddenly switched my views on whether these things are going to be more intelligent than us.”
Deep learning pioneer Geoffrey Hinton has quit Google
Hinton will be speaking at EmTech Digital on Wednesday.
The future of generative AI is niche, not generalized
ChatGPT has sparked speculation about artificial general intelligence. But the next real phase of AI will be in specific domains and contexts.
Video: Geoffrey Hinton talks about the “existential threat” of AI
Watch Hinton speak with Will Douglas Heaven, MIT Technology Review’s senior editor for AI, at EmTech Digital.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.