We’re back with another edition of Machine Learnings, brought to you by the folks at Heyday.
Heyday is an AI-powered memory assistant that resurfaces content you forgot about while you browse the web.
Most of the public progress in 2023 has been in large language models, but can we expect a shift in the second half of the year?
Huge strides are being made across machine learning, though. Perhaps we hear more about sparse networks? Any takes of your own?
-@samdebrule
What we're reading.
1/ Great leaps in human understanding often come from some new way of working, whether that’s through technological progress (like AI), or a step change in how people can use the tools needed for the job. Is that the case we find ourselves in with mathematics, today? Learn more at The New York Times >
2/ Sketch to image is here. Meet Stable Doodle, from Stability, and turn your napkin sketches into art. Learn more at Fast Company >
3/ Bill Gates has been talking AI recently. First, by sharing how he thinks it will change the world for the better. Here, he uses reason and historical reference to talk down doomerism, one argument at a time. Learn more at GatesNotes >
4/ Elon’s new AI venture is coming into frame, and not without it’s share of criticism of their path to get there. Learn more at WIRED >
5/ What happens when Google Search generates new results on the fly? I haven’t seen this detailed argument before, and I quite enjoyed it. Learn more at The Atlantic >
6/ Claude 2 is here. Let’s see why the makers think it’s safer than other chatbot technology. Learn more at Quartz >
7/ We touched on the weather last week, and the boom is real. Are we on the brink of an actual leap in forecast quality? Learn more at The MIT Technology Review >
Research for this edition of Machine Learnings was enhanced by Heyday, the AI-powered memory assistant.