Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

golden.com

Post reply on HN
Print view View original

41–50 of 70 posts

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#41

Post by Cactus2018 »

theYipster wrote: post #25

Having worked with the "original" Watson, I saw first hand how the system stumbled upon a particularly stupid but hard problem as it tried to scale. In 2014, I saw a demo of the original Discovery Advisor, which was at the time the closest commercial equivalent to the "Jeopardy system." This demo took in Wikipedia as a corpus, and a question was asked: "what country produced the greatest amount of wheat in 2012?" The…

> I'm not sure if it does now, but I do know that reading data from tables in a manner that can be easily integrated and scaled within a broader semantic processing system is quite difficult. I'm not as focused on the space as I once was, so I'm not sure if the problem has been well solved yet. If not, I'd say it's a worthy area to invest in a solution.

In R you can read data from tables like this:

    df
In google sheets

    =ImportHtml("http://en.wikipedia.org/wiki/Upper_Peninsula_of_Michigan","table",3)
In Python+Pandas

    df=pandas.read_html('https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M', header=0)[0]

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#43

Post by koosha »

theYipster wrote: post #25

Having worked with the "original" Watson, I saw first hand how the system stumbled upon a particularly stupid but hard problem as it tried to scale. In 2014, I saw a demo of the original Discovery Advisor, which was at the time the closest commercial equivalent to the "Jeopardy system." This demo took in Wikipedia as a corpus, and a question was asked: "what country produced the greatest amount of wheat in 2012?" The…

I agree.

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#44

Post by koosha »

Barrin92 wrote: post #3

hadn't heard of it. Sounds like the semantic web or Wolfram Alpha. It's very ambitious and I think almost like an AGI type problem, because parsing human queries to the point where the system can actually reason about semantics, and on its own create ontologies and relationships of everything you find on the web that are actually useful and accurate is difficult.

Congrats Jude! Proud of you.

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#45

Post by hazz99 »

Traster wrote: post #33

I feel I might be too jaded to comment on this, so let me just preface this as the view from outside silicon valley > our vision to build an extensive database and graph of knowledge for humanity, including practical commercial tools and community features to aid discovery and decisions. So you, and your, what? half dozen phds? want to produce a graph of human knowledge. Okay fine. That's a lofty goal, let's set you…

Most companies have a large vision. The creation of a far reaching vision/mission is a standard management technique that allows people to judge actions based on whatever it falls in line with the (long term) vision.

This is taught in business school. It’s not a Silicon Valley thing.

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#46

Post by tinus_hn »

theYipster wrote: post #25

Having worked with the "original" Watson, I saw first hand how the system stumbled upon a particularly stupid but hard problem as it tried to scale. In 2014, I saw a demo of the original Discovery Advisor, which was at the time the closest commercial equivalent to the "Jeopardy system." This demo took in Wikipedia as a corpus, and a question was asked: "what country produced the greatest amount of wheat in 2012?" The…

WolframAlpha actually has this data but doesn’t understand the question

what country produced the greatest amount of wheat in 2012

If you ask the suggested

country produced most wheat

You do get the table you talk about.

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#47

Post by dubcanada »

frakkingcylons wrote: post #13

Tried searching for Bach, first result besides a bunch of companies (?) is a Canadian product designer. Johann Sebastian Bach isn’t even in the first page of search results somehow.

I am confused as how it can call itself a "knowledge database" when it doesn't even have basic knowledge.

Searched for Falcon, apparently it's a company in the AI industry, has a website falcon.com.cn and is a genus of birds.

Also searched "Apple", got the company, good knowledge base. The fruit Apple is a page that says it's a fruit tree, with the CEO Tim Cook, former CEO Tim Cook, and Timothy Cook.

It seems to just be completely wrong, minus maybe a 100 articles.

I feel like basic encyclopedia information should have at least been pre-populated.

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#48

Post by zaroth »

Cactus2018 wrote: post #41
theYipster wrote: post #25

Having worked with the "original" Watson, I saw first hand how the system stumbled upon a particularly stupid but hard problem as it tried to scale. In 2014, I saw a demo of the original Discovery Advisor, which was at the time the closest commercial equivalent to the "Jeopardy system." This demo took in Wikipedia as a corpus, and a question was asked: "what country produced the greatest amount of wheat in 2012?" The…

> I'm not sure if it does now, but I do know that reading data from tables in a manner that can be easily integrated and scaled within a broader semantic processing system is quite difficult. I'm not as focused on the space as I once was, so I'm not sure if the problem has been well solved yet. If not, I'd say it's a worthy area to invest in a solution. In R you can read data from tables like this: df In google sheet…

In the problem space of “reading data from tables in a manner that can be easily integrated and scaled within a broader semantic processing system”... I would assume that “reading data from tables” isn’t the hard part.

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#49

Post by AndrewUnmuted »

gerbler wrote: post #12

Pretty slick but I think calling it "The most comprehensive knowledge platform" is a slight exaggeration. I searched for a few random topics ("urban planning", "pianos" and "bitcoin") and bitcoin was the only one to have a (lengthy) article. I also don't understand the incentive for users to contribute to a knowledge base that is then being sold: https://golden.com/pricing

It makes little sense for someone to contribute to a knowledge base like this one.

One of the quotes from the home page - supposedly written by a person who's tried it out - is as follows:

"18 years later, a startup to take on @Wikipedia --> @golden" [0]

This really confuses me. What exactly would it mean to take on Wikipedia in a meaningful sense? You'd have to build the community of Wikipedia with the same kind of values and ethics governing it, then you'd have to get the novel software (the "AI" thing they claim to be using) implemented in a way that doesn't violate said ethics, nor lowers the quality of the information.

Seems like it'd be much better just to work towards putting the AI into use at Wikipedia. Whatever innovation does end up resulting from this company, it will likely get lost if/when it gets acquired, so in the end few if any people will be able to enjoy its benefits.

[0] https://golden.com/home

Re: Golden raises $14.5M Series A led by a16z and Marc Andreessen joins board

#50

Post by smitty1110 »

narrationbox wrote: post #4

This particular field is difficult. Other than Google (through Search and also its acquisition of Metaweb), no other company has managed to achieve tremendous revenue with a knowledge base product alone. Cyc, Wolfram Alpha, the original IBM Watson (the expert system, not the ML APIs borrowing the brand) are all surviving but not thriving.

Don't forget the original knowledge base product - Bloomberg. They still bring in a lot of cash each year, but as a private company we can't get exact amounts.
Post reply on HN