This essay was originally written in December 2022 as I pondered the future of my job. I sat on it because I wasn’t sure of the optics of posting such an essay while employed by Google Brain. But then Google made my decision easier by laying me off in January. My severance check cleared, and last week, Brain and DeepMind merged into one new unit, killing the Brain brand in favor of “Google DeepMind”. As somebody with a unique perspective and the unique freedom to share it, I hope I can shed some light on the question of Brain’s existence. I’ll lay out the many reasons for Brain’s existence and assess their continued validity in today’s economic conditions. Read More
#big7Daily Archives: April 29, 2023
Why
Navigating the High Cost of AI Compute
The generative AI boom is compute-bound. It has the unique property that adding more compute directly results in a better product. Usually, R&D investment is more directly tied to how valuable a product was, and that relationship is markedly sublinear. But this is not currently so with artificial intelligence and, as a result, a predominant factor driving the industry today is simply the cost of training and inference.
While we don’t know the true numbers, we’ve heard from reputable sources that the supply of compute is so constrained, demand outstrips it by a factor of 10(!) So we think it’s fair to say that, right now, access to compute resources — at the lowest total cost — has become a determining factor for the success of AI companies.
In fact, we’ve seen many companies spend more than 80% of their total capital raised on compute resources!
In this post, we try to break down the cost factors for an AI company. The absolute numbers will of course change over time, but we don’t see immediate relief from AI companies being bound by their access to compute resources. So, hopefully, this is a helpful framework for thinking through the landscape. Read More
ChatGPT Answers Beat Physicians’ on Info, Patient Empathy, Study Finds
— Evaluators gave chatbot the better rating for responses to patient queries by a nearly 4:1 ratio
The artificial intelligence (AI) chatbot ChatGPT outperformed physicians when answering patient questions, based on quality of response and empathy, according to a cross-sectional study.
Of 195 exchanges, evaluators preferred ChatGPT responses to physician responses in 78.6% (95% CI 75.0-81.8) of the 585 evaluations, reported John Ayers, PhD, MA, of the Qualcomm Institute at the University of California San Diego in La Jolla, and co-authors.
The AI chatbot responses were given a significantly higher quality rating than physician responses (t=13.3, P<0.001), with the proportion of responses rated as good or very good quality (≥4) higher for ChatGPT (78.5%) than physicians (22.1%), amounting to a 3.6 times higher prevalence of good or very good quality responses for the chatbot, they noted in JAMA Internal Medicine. — Read More
#chatbots
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