VC Cafe
MARCH 1, 2024
I’ve recently come across several of such lists and I thought it could be useful to aggregate them and share them here. Automated Root Cause Analysis – there’s an opportunity for automated root cause analysis to substantially improve incident resolution time, and the experience for engineers.
ReadWriteStart
MARCH 31, 2011
Elbaz identified several major hurdles that companies face around data: Findability Access Rights and Ownership Economics and Business Models Standards Integration and Aggregation Trust. These are challenges for any company, arguably, but for startups, they can be particularly daunting.
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Agile VC
APRIL 17, 2011
Kayak was started here in my backyard of Boston… co-founder & CTO Paul English and the product/engineering team is based here in Concord MA. What They Do: Travel search engine. Last week ZipCar began trading and has a market cap of about $1 billion. I’m pleased to now turn to Kayak’s S-1 filing.
ConversionXL
OCTOBER 27, 2020
But every change has the potential to adjust tactics—even if that adjustment means having to do less “for search engines” because algorithms improve. In aggregate, long-tail queries can drive a ton of traffic. Text Optimizer is another useful tool that uses semantic analysis to identify underlying concepts and search patterns.
VC Cafe
JUNE 18, 2012
Unlike other companies, we are a true digital record label, not aggregators. The First Taste Engine. Jinni is a Taste Engine. With a Taste Engine, you don’t search by what you’re looking for, you search by what you like. Search engines are wonderfully adept at helping people locate what they know they want.
View from Seed
OCTOBER 7, 2015
These are still very early days for machine learning, and we’re many iterations and innovations away from a wholly independent AI that can understand all of our semantics, let alone incite the Singularity. Since around 2006, newly proven efficiencies in neural network structure and speed have improved the accuracy of document planning in NLP.
View from Seed
OCTOBER 7, 2015
These are still very early days for machine learning, and we’re many iterations and innovations away from a wholly independent AI that can understand all of our semantics, let alone incite the Singularity. Since around 2006, newly proven efficiencies in neural network structure and speed have improved the accuracy of document planning in NLP.
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