Recently it's failed to find functions by verbatim search name within single project searches. I am pretty sure it used to function better than this.
986 karma · joined May 14, 2015
Imagine what would happen if startups could not access their capital? By the time funds were available for withdrawal, the businesses would be dead. The regulators then have to track every funder to every dollar to return money. It would take a decade for this to happen.
Pop pianists don't usually play what's exactly on the page.
Eat eggs or whatever I have around with a lot of milk and a cup of coffee.
Take a shower.
Read until I don't want to anymore.
Go to work until I am hungry.
Eat something, usually around 1pm.
Take a walk.
Work a little more.
Go somewhere to play music or sit with friends.
Shower.
Go to bed when I'm tired.
Right or wrong, that is how some societies are functioning.
This person is advertising their priorities upfront. Startups might see it as a weakness. Established companies might see it as a sign of stability.
LinkedIn is a historical anomaly anyways. It's generally considered bad form to include any photo on a technical resume.
When interfacing with C languages, that can be a big penalty (depending on the complexity of the algorithm).
It will probably take two generations of developers to make this happen, but well worth it. When I was studying atmospheric science I tried to understand OpenWRF (weather research forecasting) and the barrier was too high... And I had programming experience, imagine those with none!
An open source project is only as useful as it is accessible to it's average developer base.
Software developers are often stubborn. The main result of this change will be a mess of code which follows a mix of all the styles. That removes one of the greatest beauties of the Python ecosystem, that there is a "right way" to do things.
Mathematics tells you what is not possible, but it tells you nothing about what exists. Every other discipline is separated from truth by bias in observation. And there are no perfect observers.
So, pushing "truth" is really pushing a specific perception.
That said.. you can fight against "false".
But sure, SIMD is no panacea. Especially when the latency between the vector instruction shares transistors with the previous instruction.
Thanks for the wonderful blog posts (over the years) and products.
So, I guess looking from the bottom up the system may look non-continuous and linear. But if you look from the top down, it would look continuous and non-linear.
Really, I am not sure which one is "true".
One option is to specify a polynomial function, you can specify how many coefficients you want. One of the measurements is the mean-squared-error between the line-fit and the points.
You can add as many polynomial coefficients as you want, and you will be able to decrease the mean squared error. But the more polynomial's you choose, two things will be true:
1. The line-fit will be far more likely to go through the points.
2. At points in the line where there was no data, the line will less approximate the underlying physical reality.
That same mathematical property is what is relevant here. There is nothing inherently evil about non-linearity, when the non-linear math model properly maps to the physical reality. But when you over fit a line, many of the functional solutions may be completely wrong.
The problem is a question of informational density. Biological systems are computationally very dense. Far more dense than the 4nm transistor fabrication available today, and with a far larger volume of size.
Consequentially, the computational capability of most AI systems is far lower than its biological equivalent. And as you find in most information finite discretization problems - the lower density information system will alias against the higher information system.
So, that means you will have a hierarchy/pipeline of computational stages - each aliasing reality. Eventually, you will find that your parameterization of each perceptual stage has a strange property. The size of each subsequent layer is important... but the relative computational space of each subsequent stage is even more important. Because mismatched stages results in nothing but numerical interference and noise.
And I think that is where we are today. The IQ of a krill shrimp.
- increase the volatility in virtually every financial market they touched
- be exploited by adversarial learning networks to amplify funded propaganda as news
- use poorly contrived sentiment analysis to generate incomprehensibly meaningless news headlines
These non-linear "function approximators" have absolutely unpredictable and insane non-linear behavior where learned information was non-existent or sparse.
God help us all if one of these artificial intelligence devices is driving the road and sees a red stop sign that is a square, rather than a hexagon.
Edit: Nevermind, I may have been thinking about the wrong end of the pipe.
Then they sent out advertisements to get everyone on G+. And a huge number of people clicked, without even understand what they were creating. Then all of the accounts were merged into one, that had different policies.
And so, there was no longer a profit motivation for the product.
The main thing I learned was that when using the computer, I was using it too much. Even at work as a programmer, it turns out you do not need to spend most of your time in front of a computer coding. A bit more thought outside of the digital world can allow your ideas to form clearer, and then it takes far less time to code it.