Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
Introducing Gradient Ventures
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Re: Introducing Gradient Ventures
#12https://cogniac.co/ The demo over here seems to be fabricated. Even if you provide wrong labels interactively, the performance of the classifier keeps increasing ... Picked up from https://gradient.google/portfolio/
Re: Introducing Gradient Ventures
#13I thought this was odd, from the about page > We can help you find and incorporate data sets into your first models. From cleaning data to extracting the most important features, our team can help you get your production models to market. While realizing the hardest part of a startup is everything but the tech, it seems odd they're telling AI companies they'll help with the hardest parts of the technical side, the on…
Honestly, if the answer to that is that they invest in you and you use their money to buy google cloud ml services, and you go out and find customers, that doesn't sound bad.
source: i am part of the Algorithmia team.
Re: Introducing Gradient Ventures
#14Re: Introducing Gradient Ventures
#15Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
I've been meaning to create a marketplace for data to solve this problem. The obvious issue is how to protect sensitive information (perhaps instead of selling cleaned data, the platform trains models for you on leased data). I think the problem will grow quickly as meaningful data and the tech that it enables becomes an ever growing barrier to entry against startups and slow moving enterprises alike.
Re: Introducing Gradient Ventures
#16Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
Google might have an advantage in personal data, that can be used for advertising and health, but when it comes to general data, such as image datasets and NLP datasets, they can be found in the public domain and are growing fast. There is just a specific, limited advantage to Google in datasets. Mostly for ads.
Re: Introducing Gradient Ventures
#17Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
Exactly. As a founder of an AI focused startup, it is so hard convincing VC's that data can be as valuable as revenue.
Some VC's don't even bother beyond the screening call If there is less revenue although the data we gather in the process is more valuable.
Google very well knows the true value of data and hopefully they can shake the VC world for AIs
Re: Introducing Gradient Ventures
#18Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
This is not just an issue for startups, but also for independent researchers at universities, who often can’t even replicate the successes Google and co report.
Most studies currently done in AI by Google, Amazon, etc were never replicated, and likely never will be able to, because access to data is missing.
Re: Introducing Gradient Ventures
#19Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
> they have access, and can purchase, the largest and best data sets available Google might have an advantage in personal data, that can be used for advertising and health, but when it comes to general data, such as image datasets and NLP datasets, they can be found in the public domain and are growing fast. There is just a specific, limited advantage to Google in datasets. Mostly for ads.
I think you underestimate just how far along Google is with respect to the huge amounts of raw data they handle. They've been around for 20 years now and amassed a lot of expertise handling all kinds of data imaginable at scale.
If you disagree, who would you say is ahead of Google wrt general data sets that are valuable?
Re: Introducing Gradient Ventures
#20Google (and other large tech companies that have invested in AI internally) are probably the most valuable investors, because they have access, and can purchase, the largest and best data sets available. It's hard for AI start-ups to do anything without access to the right data sets, and large companies can and have better access to that data.
This is exactly why this kind of stuff should be prohibited, and the datasets should be legally regulated. This is not just an issue for startups, but also for independent researchers at universities, who often can’t even replicate the successes Google and co report. Most studies currently done in AI by Google, Amazon, etc were never replicated, and likely never will be able to, because access to data is missing.