The last two years have been some of the most exciting and highly anticipated in Automatic Speech Recognition’s (ASR’s) long and rich history, as we saw multiple enterprise-level fully neural network-based ASR models go to market (e.g. Alexa, Rev, AssemblyAI, ASAPP, etc). The accelerated success of ASR| The Gradient
Anything that looks like genuine understanding is just an illusion.| The Gradient
This essay first appeared in Reboot. Credulous, breathless coverage of “AI existential risk” (abbreviated “x-risk”) has reached the mainstream. Who could have foreseen that the smallcaps onomatopoeia “ꜰᴏᴏᴍ” — both evocative of and directly derived from children’s cartoons — might show up uncritically in the New Yorker? More than ever, the| The Gradient
A collection of the best technical, social, and economic arguments Humans have a good track record of innovation. The mechanization of agriculture, steam engines, electricity, modern medicine, computers, and the internet—these technologies radically changed the world. Still, the trend growth rate of GDP per capita in the world's frontier| The Gradient
The debate around artist compensation in AI art, and some possible solutions to the problem| The Gradient
A mystery Large Language Models (LLM) are on fire, capturing public attention by their ability to provide seemingly impressive completions to user prompts (NYT coverage). They are a delicate combination of a radically simplistic algorithm with massive amounts of data and computing power. They are trained by playing a guess-the-next-word| The Gradient
