medius
Joined 16 years ago
Joined 16 years ago
If you are judging any dimension, say priority, then assigning percentile rating to a task (i.e where does this given task stand relative to all the others) can be quite helpful to overcome the "SuperEvenMoreImportantEmergencyBugfix" cases. This is what the article is also suggesting.
And if you end up assigning 90% percentile to more than 50% of the tasks, you know your judgement is wrong, and it can be corrected accordingly. And it can also be standardized much better across the organization. Everyone can now judge their own judgements.
Rating on multiple dimensions with low correlations important for your company, say signup rate, retention, security, etc. and adding them up is a good way to not miss something important. It's not important to assign weights. Equal weights is fine [2]
I'm finding this technique quite useful in deciding what to work on next with fewer doubts about their priority. I failed to make Trello work for this and use a spreadsheet.
[1] A Structured Approach to Strategic Decisions - https://omegaleadership.com/media/Structured_Approach_to_Str...
[2] The robust beauty of improper linear models in decision making. - https://pdfs.semanticscholar.org/8793/408a67fd4c32bd7b5483d3...
(Disclosure: I created this to help my customers at https://www.terminusapp.com)
The iPad is in perfect condition with no hardware issues. It's the software that will make it an ewaste soon.
My Android phone updates all the apps (even many OS services) without any problem.
Machine learning is something that I believe can take advantage of analog computing. A machine learning algorithm does not need highly precise or accurate representations. Most current implementations of such processing units use fewer bits (usually 8).
However, even if we use fewer bits, the engineering effort (design, layout, lithography, etc.) that goes into making the processing unit still assumes that those few bits are error free. The manufacturing process treats it like any other digital circuit. It assumes data processing part should be fault free (e.g. treat MSB and LSB the same). Digital circuits also demand higher power compared to analog versions.
If an analog circuit can be designed for such algorithms, not only could it be much faster, it will probably consume far less power. With a super high bandwidth consuming little power, an analog processing chip may give us a much better playground to try advanced algorithms. The materials can then be optimized and we might end up with something like a brain.
Brains (all animals) process far more information for the power they consume.
Digital circuits give us low level reliability and so they are really good for simple control. Analog/biology don't give us that. But they can give us a high level reliability while delegating the low level reliability to digital counterparts.
How many such techniques we haven't even discovered or technology is not there to observe such things?
I really enjoyed reading Our Mathematical Universe by Max Tegmark that explores such things.
Joining a BigCo can give $1 million (above startup salary) in 5 years with a very high probability.
He has lost all credibility as a trustworthy individual. Anything he builds will be seen as tainted by IP stolen from Google (whether true or not). Most companies will avoid doing business with him for the fear of being pulled in some lawsuit and/or bad PR. This will put a major drag on his company in attracting engineers, investment, etc. He is definitely an extremely talented engineer, but his problems may be beyond any technical ingenuity that he can come up with.
I also use this list to temporarily add HN when I want to focus. This setup works well for me.
Some of my family members and friends use WhatsApp and that's something I regret (tiny bit) not using. But I don't miss Facebook, Instagram, etc. at all.
[1] https://pi-hole.net/ [2] https://github.com/jmdugan/blocklists/blob/master/corporatio...
Are these companies unable to build a link shortener? It's also so easy to migrate off shortener service. If they can and still choose to use these shortening services, there must be other reason. And that reason is that they simply don't want to. This has nothing to do with AI.
I run a software company and one of the reasons customers say they want to migrate from their homegrown spreadsheet is because the guy who built it left. A freaking spreadsheet!
Such blog posts and probably many comments here are the perfect answer to "Tell me you don't run a real business without telling me you don't run a real business"