grandrew

Thank you for your interest honest comment. We are working on creating a fully consistent and reproducible environment and publishing it on Huggingface.

I've been in this endeavor with Surface Book 2. While the results where good, the CPU usage for software DSP killed the entire effort. Microsoft is using intel's DSP accelerator to do this. While linux technically can use intel's audio DSP I never had enough time to dig into it

Thank you for brilliant comment highligthing the OSS issues.

But I believe you're missing the main point that OP is making: OSS will _statistically_ dominate every single niche.

There are just more reasons why non-OSS software would cease to exist - so eventually Inkscape will become a de-facto standard for Illustrator things; Blender will become de-facto standard of all 3D-Max things; OBS will become a de-facto standard of all Macromedia Flash Broadcast ... oh wait ... did that happen already?

There are several options how to make harvested energy work for interstellar travel

1. Just beam it with a huge laser to the spacecraft (google for several proposed projects already in development and plans for launch) 2. Store it onboard the spacecraft and then use, with multiple options and different levels of today's technology feasibility like creating a small spinning black hole or creation of exotic matter for warp drive

First, you can just google for "logistics is a shady business"

If you want to be more specific, you can google for "carrier haulage tax evasion" - this will be just the tip of the iceberg.

Supply chain is mixed with shady practices for tax evasion, bribery, laundering and all sorts of shady things at all levels that "compete" with actual process optimization. Combined with overall opposition to automation this incapacitates any effort to make the process efficient cuz it's hard, it "steals jobs" and not easy money.

Thank you very much for support!

Yes, behind the scenes it lowers the high-level logic of Python to predicate logic, uses RETE on that predicate logic to do the fastest possible JOIN operations on the tables, and uses machine learning to extract heuristics from the task and data to enable feasible monte-carlo search for valid plans.

All that means you input the rules for the "game", and it finds the way to reach the goal, no matter how complex the interactions or data are inside.

Yes, PROLOG with modern Python syntax and mostly imperative flow, commercial database experience instead of "build everything yourself", and ML-based heuristics that are learned on the fly instead of whatever hardcoded logic the particular interpreter had.

This is sometimes referred to as "Automated planning and scheduling" or simply "AI Planning" in academia.

I'd say what this all proves is that a free market and private sector is much better at those things than a communist'y government-run project.

Supply chain is a black box with people who are aggressively not interested in transparency. So the approach is to model the black box as good as we can, and start cutting away the pieces with automation.

My thoughts :) Get the mess solved here first. As a comment on your ideas - there are extremely powerful forces that would oppose any openness in logistics as it's filled with shady gangs. We need to act together to beat them off the market.

Alternatively we could merge with the machines and all go virtual. But I am to believe that part of the humanity will remain explorers and will want to go beyond our star. That's where the physics kicks in. There simply isn't enough energy that can be mined and extracted from minerals.

HyperC is not affiliated with Asgardia aside from that one of the HyperC's founders being a long-term supporter

We're a tiny team that so far only got the confirmation that it works. The focus right now is to make the first batch of customers happy, and continue to spend effort on the metaplanner.

Btw, I advise you to take a look at the metaplanner's code. It's the definition of the planning task for the planner. So that the planner can learn to solve the planner's (it's own) task. It is leveraging the HyperC core that sits in a separate repository in the same github org.

I heard the approach was circulating in the AI planning academic circles but no one had put it together as many academically-uninteresting details needed to be cared for first. That's exactly what we did.

We are not a crypto company. Moreover, being as clean and open as possible is the only way to win the battle of the good guys vs. the bad guys in supply chain.

We're starting with small Amazon sellers. And it's just what I believe is right, the technology must take over the logistics and stop the supply chain gangs from thrashing the planet with waste. We aren't getting anywhere with the status quo.

Andrew here, the founder of HyperC. Thank you very much for your feedback, and especially for your attention and time to look at the note.

Our current and today's focus is, of course, not to send the sattelites to the sun to build the Dyson sphere but rather to automate sending average commodities from China to Amazon FBA. Everything else comes after.

And you're right, the supply chain mess isn't caused by the absense of tech (although this does contribute) but rather by the "dark" forces in the logistics world that would prefer to keep things messy and hard to trace. The entire logistics thing has historically always been a shady business. But big data is coming for the dark guys.

So the immediate plan is to build the model of the "black box" of logistics by analyzing the data we can actually collect, then use the combination of technology and HyperC's reputation-leveraged optimal financing offers to beat the shady schemes out of the market. That itself could be overly ambitious, but this is what I believe is right.

Hello HN, I'm the designer of HyperC Planning Database. Its purpose is to demonstrate that state-of-the-art autonomous planning techniques from self-driving and robotics are usable in real-world IT production environments.

We package all applicable knowledge in AI planning, automatic proof and machine learning to convert multiple data science problems into an IT database administration process.

The ultimate goal is to get as close as possible to the 'universal algorithm' which will solve things like optimal logistics, food production, dyson sphere construction plan, etc.., fully autonomously.

Hi,

I'm introducing the 2 years of hard work of our team to package classical AI planning into native Python concept.

We will soon follow-up with our ML and GP accelerators of universal heuristics that we build on top of fast-downward and our naive symbolic execution engine.

Things are not quite that simple. You can't say "because my Go app serves a single request under no load in 50us, it will serve 20'000 per core under 100% load" you'd be surprised it will not.

Modern machines are like a networked cluster themselves. You need to do a ton of work to tune both kernel and "hardware" parameters to identify bottlenecks with near-non-existing debugging tools.

There is one truth here: we used to get more performance by scaling "horizontally". Maybe it's time to "scale within"?

I have a question about how Kolmogorov complexity is related to "Human complexity" or complexity of understanding?

E.g. a program may be very complex in Kolmogorov terms, like describing 1000 random numbers - easy to understand: you have a database of numbers, and a simple procedure that would scan through it. You can also imagine some real-world microservices-based program with a good architecture and a lot of code that handles all the exception cases of incoming data, all easily understandable.

And now imagine an optimizing compiler for prolog programs. It may have much less code but the algorithm will be so complex that it might be impossible to fully understand its behaviour. E.g. fast-downward is a great example of such a program.

So I'm wondering what does Kolmogorov complexity actually tell? Or does it tell anything useful in "real"-world?

Can you pls do distcc? Thanks

DISCLAIMER: this is just an attempt to do it right :-)

Still lots of work to do with optimization and vulnerability assessment. I promise to put the sources to github when I feel that this actually worked.

Currently it uses a modified openssh code and lots of PAM and NS configuration with Auth0 JWT API, plus some config tweaks all over the system

Thanks a lot!

cjsaylor, thank you for your feedback! Yes the price is not so low I just had to have some figures to start with.

But as you may know - the $5 machine you are referencing here is not suitable for any meaningful work as you will have about 300MB of RAM after you boot it for your use - and this is about the amount or RAM you will need just for your framework to load up. So you should basically compare it with the $10 or $20 machine. Also you should take into account that the price here is the actual CPU-time - while DigitalOcean charges you the wall-hour - so I estimate the price like 5x-10x lower depending on your task.

But yes I know where to move from here - for example switching to accounting in GigaFLOPS-hour rather than machine time to allow usage of power efficient laptops for example (old laptops are usually slower but are still very energy efficient) and also for the owners of faster hardware to benefit

The absence of any authentication on both sides is arguably a disadvantage though. You may choose to compute anonymously for privacy related reasons and Junk.Systems is the only platform that allows you to do so AFAIK.

Hi! My name is Andrew and I want to introduce you a piece of junk I scratched in a couple of weeks - a CPU-ridesharing service Junk.Systems

I’ve had a few projects lately that require extremely cheap computation without any need for reliability or security - I needed just raw computation, and my demand is pretty constant.

So I calculated that I can build computing farm from used hardware and operate it profitably for the price 10 times lower than google’s preemptible machine for my projects. But building a computer farm yourself is not in trend nowadays, right? So I thought of uberizing the CPU sharing by just providing a non-privileged login to linux machines with no guarantee. If the machine gets screwed up for any reason - no prob, just reboot/reinstall/whatever. According to my calculations with current price a $10k farm will earn about $1000 in bitcoins a month so that may even be a kind of business. If the whole idea works, or course. At least, if somebody will use the computations - you can get a “free” heating source from your junk :)

I’m thinking of making the whole thing work entirely on smart contracts for the best transparency and survivability of the project - as I believe that cheap computation is the key to prosperity of the Humanity.

Please let me know what you think about this stuff and I am open for ideas and any type of collaboration, Thanks!

Hi guys! Some weeks ago I announced the plotti.co microservice - the easiest way to embed web live plots with the simplest API, here comes the second part of the service and the full story behind it.

I am announcing the Plottico Tracker Pro chrome extension - its purpose is to track values on websites or SaaS services and send the updates to plotti.co. Think of it as a specialized web scraping product - built for monitoring and controlling processes only. You can directly track data from like google analytics, cloudflare stats, your hosting provider, or almost any other public or password-protected web application. Finally, no code at all is required to plot my server CPU load and data caps as my VPS provider admin panel shows it.

So what is plottico? Plottico is the way we win the fight against machines.

Guys, we are facing the potential existential risk from artificial intelligence, no joke! Last year we saw a growing serious concern about safety of intelligent systems with some great names like Stephen Hawking and Elon Musk joining the efforts to draw attention to the problem. A few months ago I watched a Davos’16 conference panel on the state of Artificial Intelligence. Man, they had it almost the top topic for the whole panel!

So, I came up with this idea last summer but it crystallized only a few weeks ago: no matter how much everything is intelligent and automated - the final decision is still made by humans. It is us, who benefit from all the systems and machines and I want to make sure I have control over it. And how do you control something if a single person can no longer understand how the whole system works? How do you make sure everything is going right?

That is why NASA has its famous control room with all the key telemetry in one place, so do the nuclear plants, large factories, even subways and VISA has its control room. This is the idea behind plottico: to provide an easy way to monitor activities all over the scattered systems and subsystems, either for science, business, hobby or personal life.

And I take a strict approach: when everything is going in the direction of making the APIs and software more complex, plottico’s mission is to continuously make a simpler, cleaner product, with interfaces and code that are more comprehensible by humans having either technical or non-technical background.

So here is the tool that helps to monitor data from any source accessible from the web.

To make tracking more robust, I’ve implemented what I called the “entropy window selector” - it is a selector based on sift4 string-difference algorithm and aims to detect the correct textnode with tracked number even if it changes its position, IDs or CSS path.

And of course the extension is GPL, and as usual is an early beta - so feel free to throw tomatoes at me, I am prepared with a bug tracker :)

Currently I am looking for an investor and a team of civilian volunteers who are not afraid to take this fight with machines face-to-face. Human intelligence strikes back!

I am adding HTTPS and (some minimal) POST support soon!

I will be very pleased to hear what browser/OS do you use

Thank you! More interaction should definitely be on the roadmap! Not everyone likes too heavy plots though.

btw, I updated the front page with short snipptes of how it can be used for server monitoring.