HN user
If you really need to.. robione at gmail
As you can see Swarm is not a solution to having a proper action to a health check event on a container.
If a fly lands on you, we don't need to shoot you and awaken the new clone of you.
Docker has some serious flaws with respect to app health and doing something about it when it's unhealthy.
Just look at this PR that is 3years old and counting: https://github.com/moby/moby/issues/28400
This is a game changer. I've met the team and they've got something special here.
You can see one of their talks and a great discussion at a BayLISA.org meeting.
The OP is advocating for MESO - magneto-electric spin–orbit logic.
From Wikipedia - Magneto-Electric Spin-Orbit (MESO) is a technology for constructing scalable integrated circuits, which utilize spin–orbit transduction of electrons. It is intended as a replacement for the CMOS technology. Compared to CMOS, MESO circuits require less energy for switching, lower operating voltage, and feature a higher integration density.
More here: https://www.techspot.com/news/77688-intel-envisions-meso-log...
It's time for the age of graphene. SV -> GV.
It's model-blind.
While this is a great improvement, this is most needed on mobile devices.
This was especially a problem with Ingress and Pokemon Go games where you need the map to be correct where it isn't. Even more difficult is using those apps in places like the Arctic or Antarctic, there's no way to accurately place GPS coordinates, deal with game portals or have directions other than the compass.
We're not going to get very far letting machines guess what we want by making models we can't interpret.
Explainability is important, and critical in applications where lives are on the line.
Explainability where we're guessing what's happening in a black box model won't do either. Nothing but complete transparency of the model and why it's doing what it's doing. Its source code, that makes sense to humans, is needed. Full on model audit. No guessing.
I can think of only one company that's attempting to do this, and it's not anyone you hear working on explainability, including DARPA.
Karl Fant and company: http://www.theseusresearch.com/
There are a lot of reasons, some of which are cultural. With the concept of failure being shameful, those people bury that experience and try completely different ones to find success they can feel comfortable with sharing.
Not all societies view a shortcoming or failure as a learning opportunity and stepping stone to success.
Self absorbed folks and VCs often ask this exact question, "why are you the only one with this idea?" which is short sighted and impossible to answer.
Either everyone else is stupid, or too lazy to come up with a plan to do it, or a myriad of other reasons. It doesn't matter why.
Like someone else pointed out the industry timing, state of technology and funding for that matter all drive these possibilities.
In the end only execution matters, and that comes with a long list of prerequisites aligning just right to even begin to form a possible positive outcome. It's luck and determination. The rest fail anywhere in-between, only to try again a decade or so later when the cycle repeats.
Welcome to the status quo. Don't like it?
Change it.
Google finds XAI easily: https://www.darpa.mil/program/explainable-artificial-intelli...
As for the conversions, I think these guys are working on a service or with early customers. https://optimizingmind.com
There are many, just ask any unhappy scientists.
Funding goes to popularity, not new research. This is even true at DARPA where they ignore new technology because it doesn't fit some preconceived notion or don't have a framework to evaluate it.
Case in point for XAI, explainable artificial intelligence. The algorithms we use today give us black box models we can't interpret directly. So instead of fixing the algorithms, they focus on modeling the models and "guessing" which ones come close enough via simpler more intuitive stacks of models. Guesses upon guesses.
There has been research in new algorithms that generate open models where the weights make sense and are editable. There is one company working on this, but it's not nearly enough.
There's another set of research that has managed to convert black box models into open ones, giving full transparency.
Then there's asynchronous circuits research which do not require a clock. These can reduce power usage and boost efficiency on low power devices. Not much going on here.
There's one group building a RISC5 architecture with these, based on 30+ year old research with the inventor who still has not seen his life's work commercialized.
Then there's various types of imaging and tracking with signals we use every day, such as BT, Wi-Fi and Cellular among others, and being able to locate devices or people. You can find several universities doing this, none have made it commercially.
Similarly, having grown up in a Socialist Republic with a Communist party, envy was a big motivator for crime against your neighbor.
While some would never have a thought of harming another over perceived better off neighbor, most would take action as some form of irrational justice. And if they were found out or caught, the 'actual' justice would never be forgiven, despite all this being their own doing.
Many leave this type of village environment for different cultures and more maturity.
The company is a small startup with an amazing breakthrough called Optimizing Mind.
They have magical ways of 'explaining' black box models.
But it's not what DARPA is pushing (box remains black), rather the opposite, illuminating what's inside the box, making it a transparent open box. So much so, that the models they make you can edit by hand, since they make sense (to mere humans). Has rather immense implications.
Here's their crappy website: https://optimizingmind.com
There is very little, but what I have found is good work from The Math Citadel folks: https://www.themathcitadel.com/category/spire/probability-th... ,, also one in the stats category.
What I find unreasonable is doing all this without knowing what the model is doing. It's blind with no way to steer and correct it.
That is what feed forward networks and back propagation do for us. So why do we keep using them?
Then there's the statistics of it all.. what are we actually modeling? 'The real world' you say? Think again.
Data has to be changed and manipulated into i.i.d. form, or the algorithms won't work. How does an independent set of random variables give us a model of the actual dataset which is a very limited representation of the real world? It doesn't. It's modeling something else.
Okay, why don't we take dependence into account? Surely that would represent the real world better. Good question! (Shirley has nothing to do with it.)
It's because there is no formal definition of dependence in statistics. Let that sink in for a minute.
So the math needs work, statistics needs a revolution, and then we can begin to change AI enough for it to finally start making sense. Focus on explainable algorithms and actual ability to validate that what models generate make sense and will not be unlawfully biased or have outliers that will cause harm.
There appears to be only one company who has something like this. But few actually care.
Should be a better network and help with scaling.
No, this is: https://wiki.openstack.org/wiki/Ironic
The title needs a comma to clarify it's testing of terrestrial microbes was done in space. Sigh.
In reality this is a consequence of how much effort we make in remembering something.
It's well known that making lasting memories relies on multiple associations that all lead to that memory.
So when you learn someone's name for the first time, say it a few times, and think about something factually unique about the person, make those associations with things that come to mind. (ex: Benjamin, Ben, Big Ben, short Ben with a hat & side burns.)
The more you make, the better you'll be at remembering people's names and the easier it will get.
This is indeed a fascinating license, but most large corp legal teams do all they can to avoid anything with GPL ties in fear of legal issues forcing them to open proprietary code by proximity of GPL code used. Perceived risk aversion. This is short sighted.
BSL on the other hand could give large corps assurance that new technology from startups is safe to invest in, because if the startup goes away, (large % do) the code becomes open source as per this specific BSL.
This does not seem to address the case where someone chooses to simply not update a version of the BSL licensed code and its license expires while new versions maintain the BSL and extend the expiration.
It seems the licensing mechanism needs to use a blockchain type validation mechanism to stay current, transparent and accountable.
The markets weren't predictable and ran counter to the previous patterns which were already invested long or short.
The owner sent me his returns from 2007 and it's a steady upward slope, even through down times.
I just started last month, and I'm up overall, although the Trump event took some back. The system takes these draw downs into account.
If I told you I made $11K last month it's mostly meaningless since the size of the account and markets you choose are important.
So I don't have enough data for you, but the data that was shared with me was better than anything else I've tried. And I've done day trading too. This is much simpler and passive once set up.
Feel free to reach out if you want, see profile info.
I used to do index funds. Then I went looking for an active portfolio manager. After a few years I found one, he was good, but 6mo in he switched jobs and left for another career.
The next guy wasn't good and eventually didn't want to actively manage the account. I kept looking until this year when I found fractalgo, which is used by large institutional investors to trade through science without emotion and second-guessing.
Downside is you needed to be a qualified investor.
I called up the owner curious about how the fractal tech worked and found out he was setting up a service for everyone, not just the big guys.
After some research I moved my IRAs left over from previous 401Ks to a custodian that can do directed investments + broker and let the automated system go.
Couldn't be happier. No humans required once set up, and it keeps growing like a weed while I sleep.
Do your own research for what works for you and seek it out. You will find it, eventually.
Since doing so well, they just opened a fund using the same technology.
wouldn't cloudflare be more effective?
Not quite, you can only accelerate half way, then you have to decelerate the other half. (if only using this) Adding sufficient thrusters could mitigate the long deceleration.
Thruster + Ion Engine combination starts looking much better.
This is just the beginning of the tides turning. This huge jump is just a few thousand Chinese investors coming online. More will come. Next think about when another country gets its own exchange, say India. Expect more large jumps before things settle down.