91–100 of 121 posts
Earlier quoted context omitted.
That's why I wrote text search.
And because of what the text search returns you cannot link to an illustration?
A poorly-kept secret in Silicon Valley is that many "AI startups" started over the last few years are actually using humans, with a long-term plan to slowly decrease the amount of work the humans do using algorithms (generally based on machine learning, but not always) as well as more basic automation. In some cases they don't actually do any "AI" work for the company's first few years, and if they do, it's more like…
Very frustrating for companies who actually do use machine learning to solve a problem! Hard to rise above the background "AI noise" of well-funded marketing. And people are already fed up with all the AI marketing bullshit; "ebbing tide sinks all boats". One way is to offer real-time results via APIs or demos, which cannot be faked with humans due to sheer latency / volume. Another is to be active in the ML communit…
I get that on a purely technical level, but really... who cares about the implementation? If a company is solving problems it really doesn't matter, and if they're solving it better using some mix of ML and human intervention... again; who cares?
Makes sense. Law of information non-growth proves AI cannot create mutual information. Only source we know of is people. This fake AI is the future of the industry.
I guess you are talking about the second law of thermodynamics? Even humans don't violate that, the have to get the energy for generating information from somewhere, and that increases entropy.
A poorly-kept secret in Silicon Valley is that many "AI startups" started over the last few years are actually using humans, with a long-term plan to slowly decrease the amount of work the humans do using algorithms (generally based on machine learning, but not always) as well as more basic automation. In some cases they don't actually do any "AI" work for the company's first few years, and if they do, it's more like…
A poorly-kept secret in Silicon Valley is that many "AI startups" started over the last few years are actually using humans, with a long-term plan to slowly decrease the amount of work the humans do using algorithms (generally based on machine learning, but not always) as well as more basic automation. In some cases they don't actually do any "AI" work for the company's first few years, and if they do, it's more like…
It’s not a secret - it literary is what peter thiel said Palantir Technologies is - a combination of AI and humans. This combination apparently is really powerful.
Human reading a 1GB logfile looking for key words/phrases is a lot more doable.
Earlier quoted context omitted.
Do you have any specific examples of AI products that are allegedly secretly using humans (don’t bother dropping specific company names)? It strikes me as something that would only be viable in very narrow cases. Anything customer-facing and low-latency, like human language translation, image classification, or speech recognition doesn’t seem viable at even modest scale. Anything involving large amounts of data, like…
x.ai is, or at least was, powered by humans.
A poorly-kept secret in Silicon Valley is that many "AI startups" started over the last few years are actually using humans, with a long-term plan to slowly decrease the amount of work the humans do using algorithms (generally based on machine learning, but not always) as well as more basic automation. In some cases they don't actually do any "AI" work for the company's first few years, and if they do, it's more like…
Very frustrating for companies who actually do use machine learning to solve a problem! Hard to rise above the background "AI noise" of well-funded marketing. And people are already fed up with all the AI marketing bullshit; "ebbing tide sinks all boats". One way is to offer real-time results via APIs or demos, which cannot be faked with humans due to sheer latency / volume. Another is to be active in the ML communit…
For the customers, they need to be sure that the company is actually capable of solving the problem they are claiming to solve (before signing some sort of long term contract that doesn't actually make the claims the sales people put forward.) The customer's evaluation, however is distinct from that of an investors.
It is the job of an investor to determine if the startup is actually capable of having reasonable odds of successfully pursuing whatever they are claiming to be doing. If an investor is not, then for an actual startup doing machine learning, probably this is not they type of investor you want.
During the ICO pump and dump cycle one thing stuck out to me - nearly all of the ICOs were being run by people without any cryptography experience. Most had little to no software development experience. I'd suggest investors take their first step in evaluating "AI" startups similarly.
Being in the public sector, I have the joy of sitting in a lot of meetings with companies and consultants that want to sell us AI for analytics and prediction. I’m still unconvinced. The closest I’ve seen to anything useful was Watson, and all it really offered was stuff we’ve been doing for years. I mean, we have 5 people working with data and building models, and Watson could maybe automate some of that, but you’d…
Usually the problem is that companies are going to sell you an AI solution for your data, but these companies are not going to tell you that with your current data there is very little an AI system can do. I say this because I saw companies who wanted a prediction system with 2 years of data (40 datapoints per year). Any AI expert will see there is no way this will work but still the system is sold to the company. This is much worse in the public sector.
A poorly-kept secret in Silicon Valley is that many "AI startups" started over the last few years are actually using humans, with a long-term plan to slowly decrease the amount of work the humans do using algorithms (generally based on machine learning, but not always) as well as more basic automation. In some cases they don't actually do any "AI" work for the company's first few years, and if they do, it's more like…
Very frustrating for companies who actually do use machine learning to solve a problem! Hard to rise above the background "AI noise" of well-funded marketing. And people are already fed up with all the AI marketing bullshit; "ebbing tide sinks all boats". One way is to offer real-time results via APIs or demos, which cannot be faked with humans due to sheer latency / volume. Another is to be active in the ML communit…
This will pass when funding gets tight again and/or the economy enters a recession. A very sharp recession is actually good for the valley because it helps clean out the fakers; it's no different than the first cold snap in the winter helping clear away certain pests.
(One takeaway from this is that if one wants to found a startup, and one is not a fraud, it's actually better in almost every way to do so in the first part of a recession: lower salaries, less grass-is-greener attrition, lower real estate costs, etc.)
I have priced some popular computer vision APIs and found you can get a human in southeast Asia to do the work cheaper... Something seems wrong with that!!!
OpenCV is free and used for important projects at companies including Yahoo! and others.