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Looking Back On Tech, Startups, And VC In 2018

Haystack

companies, more sensitivity around technology IP and security. This was the big consumer behavior story of 2018, behind the rapid rise of digitally-native vertical brands (like the breakout , Hims), and the rise of prosumer-level data applications (like breakout Airtable). In the meantime, we have what we have today.

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Paywalls, SEO, and the Need for a Damn Good Brand

ConversionXL

If you take a random article on The Washington Post and load it into Google’s Mobile-Friendly Test , you can see that Google has no issue crawling or rendering the content: That’s because the Google Mobile-Friendly Test uses the real Googlebot user agent and IP. News is an especially challenging vertical since no site owns a newsworthy event.

SEO 122
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Search Intent: How to Analyze and Optimize Your Site

ConversionXL

But algorithms haven’t always kept pace. IP address) can provide clues to search engines, as can search history, time of year, or time of day. That context can help sites rank in a vertical like recipes, where search engines can’t differentiate a good chocolate chip cookie from a life-changing one. Geography (i.e.

Search 126
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Spectacles and $SNAP’s $20B Valuation

Austin Startup

The smartphone is for everyone, we don’t have to think the iPhone is about a certain demographic, or country or vertical market: it’s for everyone. Google also likely has the best computer vision experts, datasets, and algorithms on the planet. I think AR is that big, it’s huge. Global smartphone revenue is about $420B.

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Austin AI startups raised more than $50 Million in 2017

Austin Startup

Enterprise Platform or Vertical Business Focused. The enterprise focus has a tough time showing their own IP versus the vertical business solutions have limited total addressable market. Kintrans Sign language kiosks through machine learning algorithms. Most of the startups can be classified into two general categories.

Austin 49
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30 Machine Intelligence Startups to Watch in Israel

VC Cafe

Since AI and ML startups cut across verticals (analytics, fintech, health, adtech, security, etc), it’s easier to group them under the “machine intelligence” umbrella, coined by Shivon Zillis , a partner at Bloomberg Beta. It uses machine learning and predictive algorithms to analyze over 250 terabytes of data daily.

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Startups in stealth mode need one piece of advice - Discussion

news.ycombinator.com

We already have some competitors in the vertical and while there is no point in trying to hide the actual idea, there are differences in the way we implement stuff that can get us an advantage over the competition. >> One thing Id add: IP- and idea-defense isnt always the strategy behind the stealth tactic.

Stealth 41