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Adventures in Improving AI Economics

a16z.com

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Re: Adventures in Improving AI Economics

#21

Post by Riegerb »

andrewtbham wrote: post #15
zamadatix wrote: post #5

"Andreessen Horowitz (known as "a16z") is a venture capital firm in Silicon Valley, California" In case anyone was as confused as I was about what a16z means - it's just the company not a new abbreviated term related to AI.

What AI companies are they invested in? Labelbox is the only one I know. https://a16z.com/portfolio/

Hey—this is Brian from Labelbox. Thanks for the mention.

Martin and Matt are incredibly sharp on the trends in AI and have inspired our work at Labelbox immensely. I particularly like the discussion on getting the operations right for building and iterating with ML. Like software development, iterating quickly is key to building a performant model on real world data. The average iteration time for ML is 2-4 weeks in the industry right now. Comparing this to software development averages is stark. Getting the development and operations of ML right can greatly speed up iteration and improve the likelihood of getting to market with performant ML systems.

Re: Adventures in Improving AI Economics

#22

Post by maxbond »

ipsum2 wrote: post #7
antipaul wrote: post #4

Earlier quoted context omitted.

Perhaps. It seems it’s still an open question whether AI is just about memorizing your data, or can it actually make reliable decisions during previously unseen scenarios. Have we already observed, or collected, all that is possible in the “driving” world?

Most self-driving companies use simulations to see how the model performs in unseen scenarios.

I'm sure that's tremendously helpful but isn't exactly an antidote, is it? You can't really simulate an unforeseen situation. If you can simulate it accurately - then you've foreseen it, and are thus able to account for all relevant variables. If you are randomly generating scenarios, something like fuzz testing or property testing, then I am sure you will discover bugs before they hit production, but you can't be sure you're simulating it accurately.

For example, maybe when your car is T-boned while climbing a steep hill, the suspension behaves in a way you didn't expect and which isn't replicated by your simulation. Or maybe you're sent a batch of decals with bad adhesive, and in the hot sun the begin to slip down the windshield until they end up obscuring or otherwise interfering with a sensor.

The only simulation that can account for every variable, regardless of whether you've anticipated it, is reality.

Re: Adventures in Improving AI Economics

#23

Post by Swizec »

eanzenberg wrote: post #19

In my experience, there are just a lot of "bad" AI/ML engineers who don't fundamentally understand what data can do, what ML algorithms can handle, and how to piece it together to produce something of value to the end user. A couple of these people on a team can torpedo a project. Worse are those who sabotage projects or are general pain points of hindering progress. These may be jaded people who don't believe that M…

Correct me if I’m wrong but isn’t this fundamentally true for any team working on any project?

Re: Adventures in Improving AI Economics

#25

Post by LifeIsBio »

gilgoomesh wrote: post #14
zamadatix wrote: post #5

"Andreessen Horowitz (known as "a16z") is a venture capital firm in Silicon Valley, California" In case anyone was as confused as I was about what a16z means - it's just the company not a new abbreviated term related to AI.

Yeah, I find this kind of abbreviation annoying. But there's a few words that are commonly abbreviated like this: i18n -> internationalization l10n -> localization g11n -> globalization l12y -> localizability a11y -> accessibility It bothers me because my brain does not jump from the abbreviation to the underlying word. I really need to stop and think about each one. And I get the numbers wrong when writing them.

There was a period of a few months when I was first learning about web apps where I saw "i18n" multiple times. The first time I came across it, I tried to sound it out:

i18n -> I-one-eight-n -> iwonation

I was already a couple of rabbit holes deep at the time and didn't have the mental capacity to look it up and wrap my head around yet another new concept.

"Oh boy." I thought to myself, "One more word I've never heard of, probably representing some complicated CS concept."

I was so annoyed when I finally found out what was going on.

Re: Adventures in Improving AI Economics

#26

Post by gk1 »

One way to deal with AI/ML shortcomings I've seen is to require end-user intervention for edge cases; such as a support chatbot that transfers the customer to a human rep if it can't understand the issue. Human intervention isn't mentioned in the article but maybe they'd put that under "narrow the problem," or they may not consider that a solution since human involvement eats into margins.

I believe all software companies will be AI companies in "The critical design element is that each model addresses a global slice of data... There is no substitute, it turns out, for deep domain expertise." Totally true for marketing as well. Much more effective to define audience segments and tailor the messaging and marketing for each.

Re: Adventures in Improving AI Economics

#27

Post by KorfmannArno »

antipaul wrote: post #4
mensetmanusman wrote: post #3

Good analogy about discovery of Pharma molecules. It’s really fun to think about the fact that Tesla has more than enough data to unlock autonomous vehicles, but all that is missing is the correct AI architecture to get it working... Who will figure out how to code that? Will it be a breakthrough, or can sub-optimal architectures eventually reach equilibrium with 10x or 100x the amount of time/data processing.

Perhaps. It seems it’s still an open question whether AI is just about memorizing your data, or can it actually make reliable decisions during previously unseen scenarios. Have we already observed, or collected, all that is possible in the “driving” world?

I've yet to see an "AI" that is not just memorizing data.

Re: Adventures in Improving AI Economics

#28

Post by MisterPea »

Swizec wrote: post #23
eanzenberg wrote: post #19

In my experience, there are just a lot of "bad" AI/ML engineers who don't fundamentally understand what data can do, what ML algorithms can handle, and how to piece it together to produce something of value to the end user. A couple of these people on a team can torpedo a project. Worse are those who sabotage projects or are general pain points of hindering progress. These may be jaded people who don't believe that M…

Correct me if I’m wrong but isn’t this fundamentally true for any team working on any project?

Yeah not sure what they were getting at. There are also a lot of people who fundamentally don't know good software engineering practices and cause a ton of tech debt

Re: Adventures in Improving AI Economics

#29

Post by mijail »

I'm happy a VC is providing these insights. If the economics of AI don't make sense by helping increase profits or cutting costs... it's going to be a long road to reaching the "promised land."

I'm biased but in a lot of industries synthetic data has the potential to balance the costs from the perspective of data acquisition and preparation as well as model testing.

This article doesn't focus too much on the edge side of things but one pattern I'm seeing is that edge deployment can be notoriously resource intensive and time consuming.

Re: Adventures in Improving AI Economics

#30

Post by KorfmannArno »

KorfmannArno wrote: post #27
antipaul wrote: post #4

Earlier quoted context omitted.

Perhaps. It seems it’s still an open question whether AI is just about memorizing your data, or can it actually make reliable decisions during previously unseen scenarios. Have we already observed, or collected, all that is possible in the “driving” world?

I've yet to see an "AI" that is not just memorizing data.

But then again, how does something like the following work?

https://twitter.com/GoogleAI/status/1293970520753369088

Any idea how it could be fooled?

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