antipaul

23 ms·

241.
by antipaul 6y ago
The small problem with your kind of approach is that it would make the army of administrators and contractors like “Deloitte.” quite redundant, and then they’d actually have to do non-Bullshit Jobs!
242.
by antipaul 6y ago
What’s the big deal about type checking? I haven’t worked on large code bases, only run small ML analyses on tabular data. Can someone be concrete with the advantages and use cases?
243.
by antipaul 6y ago
The article is so true, my latest mantra at work is “engineering is more important than data science”. Everyone is buzzing about the latter, and few even realize what is the former.
244.
by antipaul 6y ago
I have a dream - and it looks like this!
245.
by antipaul 6y ago
Sounds very true to me. I'd summarize the problem as lack of real engineering leaders. It's as if programming/engineering is looked down on or not taken seriously enough. - Biotech (in Silicon Valley to boot!)
246.
by antipaul 6y ago
Dear author, Please follow-up on your last paragraph. Sincerely, A less courageous soul
247.
by antipaul 6y ago
I also _want_ to like Apple Maps. But I always need to double check business hours using Google.
248.
by antipaul 6y ago
Thanks for the reference. Here it is: “We show, however, that deep networks learned by the standard gradient descent algorithm are in fact mathematically approximately equivalent to kernel machines, a learning method that simply memorizes t
249.
by antipaul 6y ago
It’s always fascinating to apply data/results like from this paper to help evaluate the hypothesis that machine learning/AI is mostly just a rough “lookup table” or memorization.
250.
by antipaul 6y ago
Genuinely curious why not combine syntax? Do we need 2 different pipes in R? When to use which? Thanks for your thoughts!
251.
by antipaul 6y ago
Thankfully they didn’t use just any “machine learning” nor even “AI” but “advanced machine learning AI”. Phew!
252.
by antipaul 6y ago
Anyone know how many of these “features” are _already_ provided in Google GSuite/Workspace?
253.
by antipaul 6y ago
As usual with ML, I now wonder how “similar” the test set is to the training set, compared to the examples that are neither in the training set, nor the test set: TODO: 200 million - 170,000 training - 100 test ~= 199.8 million proteins
254.
by antipaul 6y ago
What size was the test set? From what I gather, training was done on 170,000 Amino Acids (features) and the resultant protein structure (labels). This is out of 200 million possible proteins. How many examples were in the test set? EDIT: Lo
255.
Tech CEOs Are Saying Goodbye to San Francisco(theinformation.com)
38 points by antipaul 6y ago|5 comments
256.
by antipaul 6y ago
Again, M1 chip shows impressive performance gains. First graph shows, what, 3-4x improvement over Intel?
257.
Apple Silicon M1 chip in MacBook Air outperforms high-end 16-inch MacBook Pro(macrumors.com)
1080 points by antipaul 6y ago|1137 comments
258.
by antipaul 6y ago
Fascinating thought. Will Apple make a standalone screen/dock to plug in your iPhone/iPad...?
259.
by antipaul 6y ago
This MBP refresh replaces the lower-end MBP which also only had 2 ports. This is a small detail that is easy to miss. The "higher-end" MBPs with 4 ports are only availabe with the intel CPUs for now
260.
by antipaul 6y ago
Not OP, but I’ve had same difficulty switching among windows. I remap “other window” shortcut to something more convenient. See https://emacs.stackexchange.com/a/3471
261.
by antipaul 6y ago
Not to mention the condescension in calling them, right off the bat, “a grumbling shuffle of ingrained habit and stubborn resistance to change”. Habit and sticking with something that works are, like, good things most of the time!
262.
Making the Case for Prediction over Explanation (2017)(psychologicalscience.org)
2 points by antipaul 6y ago|0 comments
263.
by antipaul 6y ago
Or they had no choice but to follow the AI strongman, I mean, CTO, because of bad culture. Culture eats strategy, after all.
264.
by antipaul 6y ago
I like the point you make. I think there are the AI leaders, and then there is everyone else. What is the difference? The leaders are mostly big tech, who have driven the step-change advances you describe. This, IMHO, was due to their pre-e
265.
by antipaul 6y ago
Perhaps here it would be more advisable to just describe the data, and leave inference to the reader. Prediction is hard, especially about the future ;)
266.
by antipaul 6y ago
Isn’t “Back” usually just a swipe from the left edge of the screen?? (Admittedly not 100% always and probably not on non-native apps)
267.
by antipaul 6y ago
AI as “ideology” may be a stretch, but it tends there with all the mythos behind a word like “artificial intelligence”. Naming things matters. While the head of Apple’s ML/AI strategy likes “machine intelligence” [1], I prefer “machine
268.
by antipaul 6y ago
This was a good outline of the leadership failures common in large orgs trying to get good value out of data science. Edit: In summary: “Any organization’s adoption of AI and machine learning requires three technical tools: usable digital d
269.
by antipaul 6y ago
If only we wouldn’t forget to afford the same nuance to each other in the present...
270.
by antipaul 6y ago
My personal anecdata is that yes, it does help

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