11 ways ChatGPT saves me hours of work every day, and why you'll never outcompete those who use AI effectively.
A list for those who write code:
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Interesting article on deepfakes used for social engineering attacks. e.g. fake videos of a manager asking you to send a payment or (yikes!) fakes of someone holding loved ones for ransom. Plus some ideas on how to protect from these attacks. https://t.co/6AnjghHIDH
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one example applications of this is in medical diagnosis -- you will eventually know the outcome of some related tests, but don't know it at inference time.
key insight #MultitaskLearning: "Often features become available after predictions are made. These features cant be used as inputs as they aren't available at runtime. But they can be collected and used as tasks to provide extra info during training."
https://t.co/YQ4B1Ph7uo
I've found its especially important because users find errors in some slices of data particularly troublesome, and they will lose trust in your model if it underperforms on the parts that are very obvious to humans.
I like the framing by @SnorkelAI about the need to also focus on narrow slices of application/domain specific data, not just the coarse-grained overall metrics. https://t.co/8Ne0cbRW5y
Leaders that use humor (but nothing offensive!) are "23% more respected, and seen as more competent...Employees that have bosses that use humor are 15% more satisfied and engaged." And it doesn't even need to be that funny, it's the attempt that matters.
Can humor help you out in the workplace? Today on the show, we ask @aaker and @nbagdonas about their new book Humor, Seriously. If you listen to the episode, I'll even throw in my pet frog! https://t.co/RDBzMz5J8W
Excellent introduction to #serverless computing -- covers the basics and some interesting aspects to building a well-functioning serverless application and infrastructure.
We are growing our ML Engineering team in NYC -- looking for MLEs, Data Engineers, and Back End Engineers to join a great team at Palo Alto Networks. Help protect our digital way of life! #MLjobs https://t.co/7JqsyCoU7F
"While other structured data models such as trees (XML, JSON, etc.) would offer similar flexibility, graphs do not require organizing the data hierarchically. " -- fitting into a single-parent hierarchy is always a challenge with ontologies
"Modeling data as a graph in this way offers more flexibility for integrating new sources of data, compared to the standard relational model, where a schema must be defined upfront and followed at each step." A big plus when dealing with the reality/variety of data+sources!