Earlier quoted context omitted.
There is usually something wrong with the ontologies approach as it rarely works. There is roughly two decades of evidence for this for anyone who cares to look. Five decades if you loosen the definition to include the family of logic and constraint programming - see AI Winter. There is nothing new about these ideas. It always looks and feels like it's going to work which is why humanity has persisted with it for so…
Again, Palantir is not an AI company. They are a data visualization and analytics company. So all your perfectly fine points about ontologies and AI winter are not relevant.
How Silicon Valley's Palantir Wired Washington
101–110 of 114 posts
Re: How Silicon Valley's Palantir Wired Washington
#102Earlier quoted context omitted.
There is usually something wrong with the ontologies approach as it rarely works. There is roughly two decades of evidence for this for anyone who cares to look. Five decades if you loosen the definition to include the family of logic and constraint programming - see AI Winter. There is nothing new about these ideas. It always looks and feels like it's going to work which is why humanity has persisted with it for so…
Is this ontologies within the field of AI not working, or more generally? Do you have references to any specific discussions on this? Curious as I'm doing some work of my own (well outside AI) in which developing ontologies strikes me as useful, though I'd prefer not falling into any well-worn traps. (My use is largely comping up with useful descriptive models of otherwise hairy concepts.)
Far as ontologies in general, they have a mixed, track record. They take a lot of work to create. Then, they have to be mapped to real world inputs and outputs. One way they got applied is so called business rules engines or business process management. It's like a subset of ontology approaches of past. Here's a company that uses the real thing for enterprise software with Mercury language for execution part:
http://www.missioncriticalit.com/development.html
Also, Franz Inc, of Allegro Common LISP, covers many of the same use cases as Palantir with their ontological tooling.
http://allegrograph.com/solutions-by-use/
So, there's definitely companies using it for long periods of time for real-world, use cases. Palantir just seemed to be mixing it with hype and secrecy to maximize their sale price later. ;)
Re: How Silicon Valley's Palantir Wired Washington
#103Earlier quoted context omitted.
> Yes, and that stuff takes years to build. You're missing the whole point of Palantir when you leave this as essentially a footnote. Well, I think that's their intention. Pretend to be a software tool maker, but really be a services group. However, that radically changes the investment/return story. Because software, once you make a tool, you can sell it a hundred billion times for pretty much no additional cost and…
They have core tools, but obviously the majority of their code is bridging the core tools and their client's services. Are you kidding me? If that extremely-slick dashboard (I hadn't seen it before) is representative of the quality of their UI for all their products (I actually doubt it is), as an enterprise/government company I am shocked they have not yet annihilated their competition . If it is representative, we…
Customers want dashboards and Palantir provides excellent dashboard tooling. Dashboards make people feel smart and feel like they are learning something. But dashboards are not as useful as people think and usually fail to return enough value to cover the cost. As Palantir is so expensive the bar is higher and often not met - hence the losing of customers.
Customers need data models but they don't know it yet. The charts used with models are usually not interesting if they exist at all. If you did show charts of the data models to the customer it often makes them feel dumb and out of control - few people like that. They're also dependent on you to interpret the models and customers don't like that either.
So given the choice of comforting lie or uncomfortable truth the vast majority will choose the lie. So if you're in the business of selling comforting lies don't be surprised when they fail to work.
Re: How Silicon Valley's Palantir Wired Washington
#104Earlier quoted context omitted.
Having worked in DC and SV I'm not sure DC engineers are cheap, especially the ones who can clear.
I have too. The ceiling for an engineers salary is much lower in DC. Also young people have a much lower salary as well. Some managers might be pretty close in compensation though. We are talking about DMV. Working in the city is very uncommon for big primes. All their HQs are in Tysons It's more than DC though. Big primes have satellite offices everywhere.
Re: How Silicon Valley's Palantir Wired Washington
#105Earlier quoted context omitted.
I meant generally they are generally not useful. Sometimes they are. It depends on the purpose and what you want to build and who it's for. Given that you're building a descriptive model it would depend if you're working with facts or with probabilities. If it's facts then Ontologies should work fine, for probabilities I'd recommend Bayesian techniques. The input for these are usually small. From the sounds of it you…
An ontology of technlogical mechanisms (or dynamics): https://ello.co/dredmorbius/post/klsjjjzzl9plqxz-ms8nww Particularly in economic and policy discussion, technology is just "technology". A black box. In economics, Solow's Residual is described, by Solow , as "the measure of our ignorance" of factor productivity growth influences -- it's quite literally, statistically, what's left over after accounting for labour…
2. This is true. It's worth noting such dependencies.
3. Elaborate on that.
4. That's true. There's a lot of work on that topic already that you can draw on. I remember some showing that how the cities grew was similar to how bacteria looked. Weird stuff.
Re waste. You can model it as a separate thing that goes up when certain actions happen, then starts bringing them down. Definitely should be considered.
Re: How Silicon Valley's Palantir Wired Washington
#106Earlier quoted context omitted.
Again, Palantir is not an AI company. They are a data visualization and analytics company. So all your perfectly fine points about ontologies and AI winter are not relevant.
It is an ontology company - see their website. This is how they derive their analytics and visualizations. So my points are relevant.
Re: How Silicon Valley's Palantir Wired Washington
#107Earlier quoted context omitted.
no, it very much depends on what your time is worth and the time it would take you vs. someone you pay to do a job. If I pay someone $100 to raise the value of my home $70, but it would take me 10hrs and I value my time at $100 an hour then it would cost me $1,000 to do what I hired someone to do for $100
Why would you do it in the first place? By definition your EV is $30 higher by just not doing anything.
Re: How Silicon Valley's Palantir Wired Washington
#108I cannot say enough bad things about Palantir. Their technology is worse than the free alternatives and their consultants are not worth the money. They are losing their big commercial customers because of this and now need 'Hail Mary' contracts from the US govt to remain in business. There is already a lot of information out how bad Palantir is. I hear from friends who work there that the BuzzFeed article on them is…
Re: How Silicon Valley's Palantir Wired Washington
#109Earlier quoted context omitted.
An ontology of technlogical mechanisms (or dynamics): https://ello.co/dredmorbius/post/klsjjjzzl9plqxz-ms8nww Particularly in economic and policy discussion, technology is just "technology". A black box. In economics, Solow's Residual is described, by Solow , as "the measure of our ignorance" of factor productivity growth influences -- it's quite literally, statistically, what's left over after accounting for labour…
1. In semiconductors, we get more out of stuff when we put in less energy due to shrinking the transistors. Even increasing transistors in same node doesn't always result in more work since bigger chips have slower clock rates. I think you need to look at inputs, which include time, more than fuel given it doesn't apply to a lot of things. Even human body which, as you increase fuel, will work slower due to being gor…
Fuels feed processes in which energy is crucial. Food and metabolism, almost all ore refining and metalworking, heating and cooking, and transport. Air travel (at any significant level) and Earth-to-orbit space launch are both entirely dependent on fuel-driven processes.
I didn't mention energy transmission and transformation, which is another set of mechanisms, ranging from projectiles (force-at-a-distance) to the simple machines (lever, ramp, screw, pulley, gears), linear-to-rotary and rotary-to-reciprocating transforms. Electricity, in this this ontology, is for the most part an energy transmission and transformation mechanism: to heat, motion, light, sound, etc.
3. See the Ello link for a list. The key is that the understanding is of how to do a process, which approaches some theoretical maximum efficiency. There's probably a learning curve associated, see J. Doyne Farmer and Wright's Law (related to Moore's) of process improvement.
4. You're likely thinking of Geoffrey West. There's a lot of Santa Fe Institute thinking in this idea generally.
The hygiene factors are more than just waste.
An early realisation of this came when I was considering Metcalfe's Law and the Tilly-Odlyzko refutation, of network effects. What I realised was that while yes, additional nodes tended to produce lesser value, each node also had a tendency to impose a cost to others, that being roughly constant. In a message or information network, you could consider this to be the "is this worth reading or not" cost associated with any given message.
See: https://www.reddit.com/r/dredmorbius/comments/1yzvh3/refutat...
(If you have Reddit's RES installed, set to view images, as there's a set of graphs illustrating the cost function.)
Applying that to various group communication sets, you can estimate the cost constant, and it turns out that the maximum supportable group size is a function of that constant. Among other things, Facebook manages to scale to a billion or several members by keeping the negative cost constant really, really low.
That's just one instance.
More generally, there are other phenomena which show examples of cost:
1. The Silk Road increased trade but also created a "commerce" in disease from China to Europe and versa. Similar for interactions with the New World (smallpox, syphilus).
2. Greek and Roman city engineers were conscious of location especially as regarded water flow, with the associations with disease. Clean in, dirty out. And no deisel pumps.
3. Indoor fire gives heat and cooking, but contributes to air pollution. Chimneys help.
4. Disease and epidemics limited city sizes. ~1800 London could not sustain its own population through births given the death rate. Constant in-migration was essential. Life-expectency of new arrivals was frightfully low. This improved tremendously with creation of sewers. By the end of the 19th century, solid waste, sewage, and horse metabolites (solid and liquid) were a crisis for many large cities, which had populations of hundreds of thousands of horses alone. The automobile solved a crushing pollution problem. But you got sewage, freshwater, sanitation, etc.
5. Reducing costs of something inevitably increases the amount of undesirable activity enabled. You need highly differentiated reward/punishment systems to limit these. Highway congestion, cruising, fraud, spam, advertising, etc.
6. Systemic disruptions. Here, the issue is effects which operate in difficult-to-forsee, systemic ways. CO2 and global warming, CFCs and ozone, asbestos, endocrine disrupters, nonnative species introduction, light pollution and wildlife disruption, are all examples.
Some of this overlaps with various other areas -- pollution, ecological principles, health and sanitation, etc. But I think the concept may be more general than any of these, and in terms of a technological dynamic, it has its own space, where the factors act to limit growth unless themselves specifically addressed.
Re: How Silicon Valley's Palantir Wired Washington
#110Earlier quoted context omitted.
Ad Hominem attacks like this add very little value to the discussion.
That's not an ad hominem attack, it's a statement based on reputation. Ad hominem, properly, is based on an irrelevant characteristic of the person being attacked. "I won't work for a Peter Thiel startup because he wears white shoes after Labour Day", or "... because he mixes stripes and solids". Stating that he's got a track record of founding and backing ventures with a net-negative social value, or which simply wa…
According to his Wikipage, the major things he's done: Paypal, Facebook, Y Combinator, and a couple investment/VC/Angel ventures. None of these are net-negative social value in my opinion, or at least not any more so than virtually any other big business on the planet. He's also backed an impressive number of philanthropic endeavors.
Your comment comes across as someone's angry at Thiel because of the Gawker lawsuit and/or Trump endorsement.