10 ms·

Humane execs leave company to found AI fact-checking startup

52 points by iancmceachern 2y ago

Ragnarork 2y ago
> For another, it’s next to impossible to launch a startup in 2024 without some upfront AI pitch Nitpicking on one specific sentence, but reading that feels so dumb...
- tjpnz 2y ago
  It's what got us that awful pin.
  - namaria 2y ago
    They went full waterfall. Never go full waterfall. /jk I'm aware that the original waterfall paper actually calls for frequent iteration. It reads a lot like the Agile Manifesto actually.
    - datavirtue 2y ago
      Yep. Waterfall is everyone's favorite kneejerk whipping boy.
- ryandrake 2y ago
  If you remember their original teaser videos years ago and the writing around their product when they were in Stealth Mode, it had nothing to do with AI. The sales pitch was that it was the next iteration of an iDevice-like device with a unique form factor and method of interaction. Only at the very end did they blast "AI AI AI AI" all over the marketing and rename it to "AI Pin" and have everything AI in AI their AI announcements AI talk AI about AI. It was pretty transparent what they were up to.
- __loam 2y ago
  This was true like 8 months ago but investors are getting wise to it.
ripbasarur 2y ago
Their track record based on Humane AI does not exactly give the confidence on building an AI search you can trust. Also what a pivot from hardware to fact-checking?
- tjpnz 2y ago
  Two reasons commonly cited: - The perception that founders with big tech "credentials" stand a better chance of success than those without. The founders of Humane were ex-Apple. - The idea that founders will generally be more successful on their second try, even if their first ended up being a complete trash fire - see Adam Neumann's new venture. This one sounds more reasonable on the surface but I've got no data to back it.
  - vinni2 2y ago
    ex-Apple doesn’t really give much credibility either. For a hardware startup yes but for a AI fact-checking startup? unsure.
    - beAbU 2y ago
      Shh dont tell the investors.
    - sameoldtune 2y ago
      That was their foot in the door to the startup scene. Now they are venerable founders with a proven track record of AI-driven solutions /s
  - dmitrygr 2y ago
    I am not sure that ex-Apple is really worth anything here. Apple is a kingdom. Unless you are Tim or one of his close team, your opinion on product does not matter, you will do what you are told. So, unless you are one of those few people, "ex-Apple" means that you are very good at executing on things you were clearly told to do. I would gladly hire any ex-Apple engineer and be sure to get a great hire! But hiring ex-Apple product people...
  - 2y ago
hangonhn 2y ago
I don't know why the title is written the way it is. It's slightly different from the title on the article -- "Humane execs leave company to found AI fact-checking startup". The current link title "AI Humane execs leave company to found AI fact-checking startup" reads like an AI running the company Humane left to start its own AI powered fact-checking startup. It's very Kafkaesque and funny but maybe a bit inaccurate.
- aniviacat 2y ago
  I find the title of the article to be confusing/ambiguous. If you're not familiar with the company, "humane" could easily be read as an adjective here.
frizlab 2y ago
These guys have way too much money…
- twojobsoneboss 2y ago
  Correction: These _investors_ have too much money Actually it’s a step further: these _LPs_ have too much money
alain94040 2y ago
Ken Kocienda is known for writing the iPhone software keyboard, an experience he wrote a book about that is well worth a read.
ypeterholmes 2y ago
I'm curious- what's their strategy for determining what's true? Is it an Orwellian setup where certain media organizations (eg. NYT, Reuters, Wikipedia) are deemed to be an authoritative ministry of truth?
- torlok 2y ago
  Does it matter what their strategy is? This is vaporware. People consume information through search engines and platforms. If there's a market for fact-checking AI, it'll probably be developed in-house, since all the big companies have in-house tech. The most they can hope for is to grab as large of a bag as they can before this bubble pops, or hope they'll get bought out in a few years.
- mike_hearn 2y ago
  The article explains that: > Infactory will pull information directly from trusted resources Of course it means assuming anything the NYT says is true. Biden is sharp as a tack, it's a fact! Nah, actually the article says they'll avoid politics. They want to be a better Bloomberg Terminal apparently, and only focus on quantitative data for business purposes. Basically OurWorldInData + LLMs. In theory you can actually do a reasonable job of this sans Orwell. You train a model on a really wide selection of sources and then get it to spit out the knowledge that doesn't seem to have any disagreement within the dataset. The assumption is that no disagreement = fact. This heuristic isn't bad, but it's been tried before and is prone to errors in a few well known cases. Google tried it years ago, predating LLMs. It worked well for things like "how high is the Eiffel tower" but unsurprisingly one place it worked poorly is political ideology and terminology. Different political tribes often have their own ways of using language. Example: "is George Bush a war criminal"? Turns out that the internet is full of documents asserting this to be true, and not many asserting it to be false. This isn't because it's a widely agreed fact. It's because the left believe the concept of war criminal makes sense and can be applied liberally, but the right doesn't. Presented with this statement the right tend to say, a criminal according to which court and which government? The left say according to international law which is again, a concept the right doesn't really recognize as being legitimate to begin with because they think that law inherently flows from the concept of a nation state or empire, not a group of NGOs. At heart the "problem", if you want to call it that, is that the left is generally more passionate about politics and power so if they believe in a concept they do things like take poorly paid journalism jobs and write lots of articles that take for granted the legitimacy of their ideological precepts. The right do things like go work in banking or agriculture or oil, or indeed the tech industry, and don't end up with much time to spend arguing with them. So these concepts filter into the dataset without pushback. Deploy them in real world debate though, and suddenly you get that pushback. (this seems to be one of the reasons that a naively trained LLM ends up super woke - the internet is just left biased due to the greater output of words from that tribe) Fortunately there's a limited number of cases like this. The set of such cases does grow over time, but at a relatively slow rate. In theory, if you had people really and truly committed to neutrality and pursuit of truth, you could use LLMs to find claims that are both lacking in disagreement and also non-dependent on ideological disputed concepts. LLMs are actually pretty good at the sort of vagueness and nuance that understanding requires. The problem is that such a program would be very boring and not commercially useful. Ironically, the very concept of fact checking is itself an "is George Bush a war criminal" type problem. The right take it for granted that reality is complex and depends on perspective, the left take for granted that reality is simple and can be painted in black/white, correct/incorrect. So the right doesn't spend much time on "fact checking" as a concept, because they see it as a quasi-illegitimate endeavor to begin with. From their POV there isn't actually much disagreement on things that are genuinely empirical facts like the speed of light or the price of USD:GBP yesterday at noon, so what fact checkers end up spending time on is in reality a sort of political censorship / propaganda operation aimed at shutting down any viewpoint they don't like. So an AI dedicated to genuine checking of empirical facts would probably find that there isn't much to do. People are pretty good at agreeing on facts already, there are not that many errors to fix (and the errors that do sneak through are rarely important). An AI dedicated to the sort of fact checking that Snopes engages in would be very busy indeed, but there are plenty of people willing to work for peanuts to engage in ideological warfare against the right so where's their commercial edge? Seems like another business failure waiting to happen.
pseudopersonal 2y ago
How do egregiously failed execs continue to get funding and high profile gigs? It's not just with Humane. I've seen this with the Better.com founder, his second failure after UNCLE, and with execs from MSFT Xbox. I can't for the life of me understand how they continue to get opportunities. And how do I get in on it?
- mgh2 2y ago
  Hypothesis: most VCs have a hive mentality and would prefer betting on low risk founders through their network of "highly accomplished" individuals: usually white males - false aura of achievement, survivorship and in-group bias, Matthew effect.
  - munificent 2y ago
    Sounds about right to me. In-group membership tends to be sticky. People can stay in a tribe even when their qualifications in someone outside of the tribe would be insufficient to let them in. I imagine that's partially driven by a feeling that one's previous qualifications lend some predictive power that they will earn their place again in the future even if right now they're foundering. Also, I suspect a lot of it is that people don't want to be in groups where it's too easy to get kicked out because it makes themselves feel to tenuous. So the kinds of in-groups that stick around are the ones that are a little more generous to their members once they get in.
- goalonetwo 2y ago
  The skills required to become an exec are a lot of pitching yourself and networking to the right person to get your next job. Those skills are only slightly correlated with how good you actually are as an exec. Add to this that most companies don't like to take risks and will only hire an exec that has already be an exec somewhere else. To some level, once you make it through the exec glass ceiling, you are almost always guaranteed to always be an exec somewhere. You see this all over the place by the way. I have seen the same thing for Directors, Principal engineers etc. Those people were not always that good at their job to justify their positions. But they for sure knew how to market themselves and interview well.
datavirtue 2y ago
Big fat eye roll. The service will be redundant before it is even launched.
deleted 2y ago
[deleted]
fsckboy 2y ago
in terms of AI's making us smarter, so far, AI-such-as-we-know-it provides a greater advantage (labor saving) for traditionally smart people (who are less likely to be led astray by bullshit) than it does as a substitute for the being actually smart part. I love using it to write code or answer questions better than simple websearches, but man it produces some nonsense just as do websearches.

52 points by iancmceachern 2y ago

> For another, it’s next to impossible to launch a startup in 2024 without some upfront AI pitch Nitpicking on one specific sentence, but reading that feels so dumb...

tjpnz 2y ago
It's what got us that awful pin.
- namaria 2y ago
  They went full waterfall. Never go full waterfall. /jk I'm aware that the original waterfall paper actually calls for frequent iteration. It reads a lot like the Agile Manifesto actually.
  - datavirtue 2y ago
    Yep. Waterfall is everyone's favorite kneejerk whipping boy.
ryandrake 2y ago
If you remember their original teaser videos years ago and the writing around their product when they were in Stealth Mode, it had nothing to do with AI. The sales pitch was that it was the next iteration of an iDevice-like device with a unique form factor and method of interaction. Only at the very end did they blast "AI AI AI AI" all over the marketing and rename it to "AI Pin" and have everything AI in AI their AI announcements AI talk AI about AI. It was pretty transparent what they were up to.
__loam 2y ago
This was true like 8 months ago but investors are getting wise to it.

ripbasarur 2y ago

Their track record based on Humane AI does not exactly give the confidence on building an AI search you can trust. Also what a pivot from hardware to fact-checking?

tjpnz 2y ago
Two reasons commonly cited: - The perception that founders with big tech "credentials" stand a better chance of success than those without. The founders of Humane were ex-Apple. - The idea that founders will generally be more successful on their second try, even if their first ended up being a complete trash fire - see Adam Neumann's new venture. This one sounds more reasonable on the surface but I've got no data to back it.
- vinni2 2y ago
  ex-Apple doesn’t really give much credibility either. For a hardware startup yes but for a AI fact-checking startup? unsure.
  - beAbU 2y ago
    Shh dont tell the investors.
  - sameoldtune 2y ago
    That was their foot in the door to the startup scene. Now they are venerable founders with a proven track record of AI-driven solutions /s
- dmitrygr 2y ago
  I am not sure that ex-Apple is really worth anything here. Apple is a kingdom. Unless you are Tim or one of his close team, your opinion on product does not matter, you will do what you are told. So, unless you are one of those few people, "ex-Apple" means that you are very good at executing on things you were clearly told to do. I would gladly hire any ex-Apple engineer and be sure to get a great hire! But hiring ex-Apple product people...
- 2y ago

hangonhn 2y ago

I don't know why the title is written the way it is. It's slightly different from the title on the article -- "Humane execs leave company to found AI fact-checking startup". The current link title "AI Humane execs leave company to found AI fact-checking startup" reads like an AI running the company Humane left to start its own AI powered fact-checking startup. It's very Kafkaesque and funny but maybe a bit inaccurate.

aniviacat 2y ago
I find the title of the article to be confusing/ambiguous. If you're not familiar with the company, "humane" could easily be read as an adjective here.

frizlab 2y ago

These guys have way too much money…

twojobsoneboss 2y ago
Correction: These _investors_ have too much money Actually it’s a step further: these _LPs_ have too much money

alain94040 2y ago

Ken Kocienda is known for writing the iPhone software keyboard, an experience he wrote a book about that is well worth a read.

ypeterholmes 2y ago

I'm curious- what's their strategy for determining what's true? Is it an Orwellian setup where certain media organizations (eg. NYT, Reuters, Wikipedia) are deemed to be an authoritative ministry of truth?

torlok 2y ago
Does it matter what their strategy is? This is vaporware. People consume information through search engines and platforms. If there's a market for fact-checking AI, it'll probably be developed in-house, since all the big companies have in-house tech. The most they can hope for is to grab as large of a bag as they can before this bubble pops, or hope they'll get bought out in a few years.
mike_hearn 2y ago
The article explains that: > Infactory will pull information directly from trusted resources Of course it means assuming anything the NYT says is true. Biden is sharp as a tack, it's a fact! Nah, actually the article says they'll avoid politics. They want to be a better Bloomberg Terminal apparently, and only focus on quantitative data for business purposes. Basically OurWorldInData + LLMs. In theory you can actually do a reasonable job of this sans Orwell. You train a model on a really wide selection of sources and then get it to spit out the knowledge that doesn't seem to have any disagreement within the dataset. The assumption is that no disagreement = fact. This heuristic isn't bad, but it's been tried before and is prone to errors in a few well known cases. Google tried it years ago, predating LLMs. It worked well for things like "how high is the Eiffel tower" but unsurprisingly one place it worked poorly is political ideology and terminology. Different political tribes often have their own ways of using language. Example: "is George Bush a war criminal"? Turns out that the internet is full of documents asserting this to be true, and not many asserting it to be false. This isn't because it's a widely agreed fact. It's because the left believe the concept of war criminal makes sense and can be applied liberally, but the right doesn't. Presented with this statement the right tend to say, a criminal according to which court and which government? The left say according to international law which is again, a concept the right doesn't really recognize as being legitimate to begin with because they think that law inherently flows from the concept of a nation state or empire, not a group of NGOs. At heart the "problem", if you want to call it that, is that the left is generally more passionate about politics and power so if they believe in a concept they do things like take poorly paid journalism jobs and write lots of articles that take for granted the legitimacy of their ideological precepts. The right do things like go work in banking or agriculture or oil, or indeed the tech industry, and don't end up with much time to spend arguing with them. So these concepts filter into the dataset without pushback. Deploy them in real world debate though, and suddenly you get that pushback. (this seems to be one of the reasons that a naively trained LLM ends up super woke - the internet is just left biased due to the greater output of words from that tribe) Fortunately there's a limited number of cases like this. The set of such cases does grow over time, but at a relatively slow rate. In theory, if you had people really and truly committed to neutrality and pursuit of truth, you could use LLMs to find claims that are both lacking in disagreement and also non-dependent on ideological disputed concepts. LLMs are actually pretty good at the sort of vagueness and nuance that understanding requires. The problem is that such a program would be very boring and not commercially useful. Ironically, the very concept of fact checking is itself an "is George Bush a war criminal" type problem. The right take it for granted that reality is complex and depends on perspective, the left take for granted that reality is simple and can be painted in black/white, correct/incorrect. So the right doesn't spend much time on "fact checking" as a concept, because they see it as a quasi-illegitimate endeavor to begin with. From their POV there isn't actually much disagreement on things that are genuinely empirical facts like the speed of light or the price of USD:GBP yesterday at noon, so what fact checkers end up spending time on is in reality a sort of political censorship / propaganda operation aimed at shutting down any viewpoint they don't like. So an AI dedicated to genuine checking of empirical facts would probably find that there isn't much to do. People are pretty good at agreeing on facts already, there are not that many errors to fix (and the errors that do sneak through are rarely important). An AI dedicated to the sort of fact checking that Snopes engages in would be very busy indeed, but there are plenty of people willing to work for peanuts to engage in ideological warfare against the right so where's their commercial edge? Seems like another business failure waiting to happen.

pseudopersonal 2y ago

How do egregiously failed execs continue to get funding and high profile gigs? It's not just with Humane. I've seen this with the Better.com founder, his second failure after UNCLE, and with execs from MSFT Xbox. I can't for the life of me understand how they continue to get opportunities. And how do I get in on it?

mgh2 2y ago
Hypothesis: most VCs have a hive mentality and would prefer betting on low risk founders through their network of "highly accomplished" individuals: usually white males - false aura of achievement, survivorship and in-group bias, Matthew effect.
- munificent 2y ago
  Sounds about right to me. In-group membership tends to be sticky. People can stay in a tribe even when their qualifications in someone outside of the tribe would be insufficient to let them in. I imagine that's partially driven by a feeling that one's previous qualifications lend some predictive power that they will earn their place again in the future even if right now they're foundering. Also, I suspect a lot of it is that people don't want to be in groups where it's too easy to get kicked out because it makes themselves feel to tenuous. So the kinds of in-groups that stick around are the ones that are a little more generous to their members once they get in.
goalonetwo 2y ago
The skills required to become an exec are a lot of pitching yourself and networking to the right person to get your next job. Those skills are only slightly correlated with how good you actually are as an exec. Add to this that most companies don't like to take risks and will only hire an exec that has already be an exec somewhere else. To some level, once you make it through the exec glass ceiling, you are almost always guaranteed to always be an exec somewhere. You see this all over the place by the way. I have seen the same thing for Directors, Principal engineers etc. Those people were not always that good at their job to justify their positions. But they for sure knew how to market themselves and interview well.

datavirtue 2y ago

Big fat eye roll. The service will be redundant before it is even launched.

deleted 2y ago

[deleted]

fsckboy 2y ago

in terms of AI's making us smarter, so far, AI-such-as-we-know-it provides a greater advantage (labor saving) for traditionally smart people (who are less likely to be led astray by bullshit) than it does as a substitute for the being actually smart part. I love using it to write code or answer questions better than simple websearches, but man it produces some nonsense just as do websearches.