I don't know if it's all in my mind, but Microsoft's targeted advertising in its apps' come across as extremely tacky. Everyone else is probably collecting the same data but it feels less slimey on the surface.
I can't see how being used as training data has anything to do with this problem. Being able to differentiate between the AI slop and the accurate information is the issue.
Backpropagation Through Time (BPTT) is an adaptation of backpropagation used for training recurrent neural networks (RNNs), which are designed to process sequences of data and have internal memory. Because the output at a given time step might depend on inputs from previous time steps, the forward pass involves unfolding the RNN through time, which essentially converts it into a deep feedforward neural network with shared weights across the time steps. The error for each time step is computed, and then BPTT is used to calculate the gradients across the entire unfolded sequence, propagating the error not just backward through the layers but also backward through the time steps. Updates are then made to the network weights in a way that should minimize errors for all time steps. This is computationally more involved than standard backpropagation and has its own challenges such as exploding or vanishing gradients"
I personally know my attention span will not be 100% driving for 3 hours straight, a short break is necessary and parking, ordering a coffee can take a bit longer than you'd think.
Hah, if only you've seen me in my ICE car.
Plenty of hoping and praying the glimmering fuel light doesn't die out and that I'll make it to the fuel station.
No peace mind of mind.
Thanks for your reply, you raise a very good point, transformer models are a lot more complex. I'd argue conceptually they're the same, just the data and process is more abstracted. Autoencoded data implies using efficient representations, basically semantically abstracted data and opting for measures like back propagation through time.
If you read their account, they actually believe they would've made it there without stopping to charge, also they used a fast charging station on the trip which would've charged to 80% in 30 minutes (a much more usual break on a long 3 hour trip). Many people stop for lunch on their way to Kruger, I suspect they did this here.
Charging overnight on the slowest plug point in Kruger also delivered up to 210km range, double what they needed per day in Kruger.
It's not really an issue they were just extremely cautious, something you'd expect in South Africa if you know anything about their power grid.
I believe the author was actually trying to show it is actually feasible and range is not a concern.
Yes to both, the "neuron" would basically be a weighted parameter.
A parameter is an expression, it's a mathematical representation of a token and it's probabilistic weighting (theyre translated from input or to output token lists entering and exiting the model).
Usually tokens are pre-set small groups of character combinations like "if " or "cha" that make up a word/sentence.
The recorded path your value takes down the chain of probabilities would be the "neural pathway" within the wider "neural network".
Someone please correct me if I'm wrong or my terminology is wrong.
A good example is Venezuela, this was a car crash in slow motion. I remember the incremental changes made to law being reported right throughout Hugo Chávez' term in office right from the beginning. He was wildly popular everyone trusted him, many warned of its implications each time a law was proposed and reported. And here we are today, Venezuela is a dictatorship.
As the saying goes, it happens slowly and then all at once.
Your points are all valid, you've perhaps convinced me to give it a go again. Only thing I'd add is walking for 2 hours in total a day every single day is hardly feasible.
I would hope people exercise to a limited extent anyway, to the extent their bodies will try retain a baseline level of muscle-stength needed day to day.
As you've read on my other comment, I lost 20kg over 6 months on a low carb, low sugar, higher protein diet.
I started gyming about 4/5 months in and I personally attribute this gyming with a chain-reaction that led to me putting the weight back on and am now in a much worse position health wise, even muscle wise. This all due to practical reasons, such as increased appetite which upset the hard-fought dietary and hunger equilibrium I reached.
Exercising too is I'm sure definitely better but I feel is way more difficult and sets many, on the weightloss journey, up to fail.
I actually lost 20kg over 6 month, roughly following this advice. Not strictly, like I would be more lenient on weekends with carbs & booze, and have sugar, like a small dark chocolate, but only at night (to avoid further craving and consumption the whole day).
I avoided the exercise as it made me unbearably hungry.
Absolutely true but only to an extent.
Losing weight has long term health benefits.
Despite sustained exercise, if you are overweight you remain at higher risk of things like heart disease.
It also makes exercise more difficult decreasing the amount of exercise you'll get over the longer term.
And more practically speaking the relationship is assymetric. It's significantly more practical to restrict calorie consumption than to burn the equivalent level of calories through exercise (even without considering the impact it has on appetite and on the mind, where you think you deserve to eat more as a result).