Andrej Karpathy, one of the Heroes of Deep Learning who currently works at OpenAI, quipped, “The hottest programming language is English.” While I appreciate the sentiment...
Andrej Karpathy, one of the Heroes of Deep Learning who currently works at OpenAI, quipped, “The hottest programming language is English.” While I appreciate the sentiment...
Improvements in chatbots have opened a market for bots integrated with dating apps. I’m concerned that AI romantic partners create fake relationships that displace, rather than strengthen, meaningful human relationships.
Improvements in chatbots have opened a market for bots integrated with dating apps. I’m concerned that AI romantic partners create fake relationships that displace, rather than strengthen, meaningful human relationships.
While AI is a general-purpose technology that’s useful for many things, it isn’t good for every task under the sun. How can we decide which concrete use cases to build? If you’re helping a business figure out where to apply AI, I’ve found the following recipe useful as a brainstorming aid…
While AI is a general-purpose technology that’s useful for many things, it isn’t good for every task under the sun. How can we decide which concrete use cases to build? If you’re helping a business figure out where to apply AI, I’ve found the following recipe useful as a brainstorming aid…
I’d like to share a part of the origin story of large language models that isn’t widely known. A lot of early work in natural language processing (NLP) was funded by U.S. military intelligence agencies that needed machine translation and speech recognition capabilities.
I’d like to share a part of the origin story of large language models that isn’t widely known. A lot of early work in natural language processing (NLP) was funded by U.S. military intelligence agencies that needed machine translation and speech recognition capabilities.
Machine learning development is an empirical process. It’s hard to know in advance the result of a hyperparameter choice, dataset, or prompt to a large language model (LLM).
Machine learning development is an empirical process. It’s hard to know in advance the result of a hyperparameter choice, dataset, or prompt to a large language model (LLM).
An increasing variety of large language models (LLMs) are open source, or close to it. The proliferation of models with relatively permissive licenses gives developers more options for building applications.
An increasing variety of large language models (LLMs) are open source, or close to it. The proliferation of models with relatively permissive licenses gives developers more options for building applications.
Do large language models understand the world? As a scientist and engineer, I’ve avoided asking whether an AI system “understands” anything. There’s no widely agreed-upon, scientific test for whether a system really understands — as opposed to appearing to understand —
Do large language models understand the world? As a scientist and engineer, I’ve avoided asking whether an AI system “understands” anything. There’s no widely agreed-upon, scientific test for whether a system really understands — as opposed to appearing to understand —
Internalizing this mental framework has made me a more efficient machine learning engineer: Most of the work of building a machine learning system is debugging rather than development.
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