Technology
The Fastest Startups to Hit $1 Billion Valuations
For the founders coding in the trenches of Silicon Valley, achieving the status of a “unicorn” is still the Holy Grail. The term, which references the presumably rare and mythological uni-horned creature, is used to describe a tech startup that has hit a $1 billion valuation or more.
At the time the term was coined, unicorns were indeed rare. Aileen Lee’s data from 2003-2013 showed that just four unicorns were born a year, and that only 39 existed as of November 2013. However, while actual unicorns continue to be (very) difficult to find, the ones of the tech variety have been proliferating like bunnies.
By the count of VentureBeat, there are now 229 of them with a cumulative $1.3 trillion valuation.
The Unicorn Baby Boom
Fleximize recently created an interactive visualization that breaks down the fastest startups to reach a $1 billion valuation by geography, sector, year, and also the timeframe needed to reach the mark. We’ve pulled out the key visuals in this post, but we highly recommend viewing their interactive list which provides data on each company as well.
We’ll show the whole list of unicorns later in this article, but for now we will focus on the high level stuff: how many more unicorns are being born? Are startups achieving unicorn status faster than before?
Unicorn Births Per Year
The above chart shows unicorn births each year from 2005 until today. There’s two important things to consider here:
Time to Achieve Unicorn Status: Despite the current froth in the venture capital market, it appears that the amount of time it takes to become a unicorn has remained relatively consistent. The average is around six years to go from the founding of the company to a $1 billion+ valuation.
More Unicorn Births: While it takes the same amount of time to become a unicorn, tech culture has become much more mainstream. Today, millions of startups are launched each year and 90% of them fail. However, the ones that get past the gauntlet raise billions of dollars from VCs.
According to the above chart, there were 65 new unicorns in 2014, and an additional 91 in 2015.
Unicorns by Birthplace
The majority of unicorns are still born in North America, which holds 61.4% of the population. However, Asia is rising fast with 58 unicorns (26.0%). It’s also worth noting that Asian unicorns spend a little less time in the womb, taking five years to be born. This is comparatively lower to the international average of six years.
Unicorns by Profession
The unicorns that are born the fastest are ones focused on industries such as real estate, on-demand, social media, or e-commerce. These took four or less years on average.
Education tech and media companies took a long time to reach unicorn status – 16 years and 12 years respectively. That said, the dataset is quite small with only five companies in these categories combined.
The Fastest Startups (The Whole List)
Below is the full list of companies valued at $1 billion or more.
The absolute fastest startup?
It’s Jet.com, an online retailer said to possibly rival Amazon, that uses real-time pricing algorithms to give consumers better deals. It hit a $1 billion valuation in just four months in 2015.
Technology
Visualizing the Top U.S. States for AI Jobs
Nearly 800,000 AI jobs were posted in the U.S. throughout 2022. View this graphic to see a breakdown by state.

Visualizing the Top U.S. States for AI Jobs
Much ink has been spilled over fears that artificial intelligence (AI) will eliminate jobs in the economy. While some of those fears may be well-founded, red-hot interest in AI innovation is creating new jobs as well.
This graphic visualizes data from Lightcast, a labor market analytics firm, which shows how many AI-related jobs were posted in each state throughout 2022.
In total there were 795,624 AI jobs posted throughout the year, of which 469,925 (59%) were in the top 10. The full tally is included in the table below.
Rank | State | Number of job postings | % of total |
---|---|---|---|
1 | California | 142,154 | 17.9% |
2 | Texas | 66,624 | 8.4% |
3 | New York | 43,899 | 5.5% |
4 | Massachusetts | 34,603 | 4.3% |
5 | Virginia | 34,221 | 4.3% |
6 | Florida | 33,585 | 4.2% |
7 | Illinois | 31,569 | 4.0% |
8 | Washington | 31,284 | 3.9% |
9 | Georgia | 26,620 | 3.3% |
10 | Michigan | 25,366 | 3.2% |
11 | North Carolina | 23,854 | 3.0% |
12 | New Jersey | 23,447 | 2.9% |
13 | Colorado | 20,421 | 2.6% |
14 | Pennsylvania | 20,397 | 2.6% |
15 | Arizona | 19,514 | 2.5% |
16 | Ohio | 19,208 | 2.4% |
17 | Maryland | 16,769 | 2.1% |
18 | Minnesota | 11,808 | 1.5% |
19 | Tennessee | 11,173 | 1.4% |
20 | Missouri | 10,990 | 1.4% |
21 | Oregon | 10,811 | 1.4% |
22 | Washington, D.C. | 9,606 | 1.2% |
23 | Indiana | 9,247 | 1.2% |
24 | Connecticut | 8,960 | 1.1% |
25 | Wisconsin | 8,879 | 1.1% |
26 | Alabama | 7,866 | 1.0% |
27 | Kansas | 7,683 | 1.0% |
28 | Arkansas | 7,247 | 0.9% |
29 | Utah | 6,885 | 0.9% |
30 | Nevada | 6,813 | 0.9% |
31 | Idaho | 6,109 | 0.8% |
32 | Oklahoma | 5,719 | 0.7% |
33 | Iowa | 5,670 | 0.7% |
34 | South Carolina | 4,928 | 0.6% |
35 | Louisiana | 4,806 | 0.6% |
36 | Kentucky | 4,536 | 0.6% |
37 | Nebraska | 4,032 | 0.5% |
38 | Delaware | 3,503 | 0.4% |
39 | New Mexico | 3,357 | 0.4% |
40 | Rhode Island | 2,965 | 0.4% |
41 | New Hampshire | 2,719 | 0.3% |
42 | Hawaii | 2,550 | 0.3% |
43 | Mississippi | 2,548 | 0.3% |
44 | Maine | 2,227 | 0.3% |
45 | South Dakota | 2,195 | 0.3% |
46 | Vermont | 1,571 | 0.2% |
47 | North Dakota | 1,227 | 0.2% |
48 | Alaska | 970 | 0.1% |
49 | West Virginia | 887 | 0.1% |
50 | Montana | 833 | 0.1% |
51 | Wyoming | 769 | 0.1% |
The following chart adds some context to these numbers. It shows how the percentage of AI job postings in some of the top states has changed since 2010.
We can see that California quickly became the primary destination for AI jobs in the early 2010s, presumably as Silicon Valley companies began developing the technology.
California’s share has since declined, with a significant number of jobs seemingly moving to Texas. In fact, many tech companies are relocating to Texas to avoid California’s relatively higher taxes and cost of living.
The 10 Most In-Demand Specialized Skills
Lightcast also captured the top 10 specialized skills that were required for AI-related jobs. These are listed in the table below.
Skill | Frequency (number of postings) | Frequency (% of postings) |
---|---|---|
Python | 296,662 | 37% |
Computer Science | 260,333 | 33% |
SQL | 185,807 | 23% |
Data Analysis | 159,801 | 20% |
Data Science | 157,855 | 20% |
Amazon Web Services | 155,615 | 19% |
Agile Methodology | 152,965 | 19% |
Automation | 138,791 | 17% |
Java | 133,856 | 17% |
Software Engineering | 133,286 | 17% |
If you’re interested in a career that focuses on AI, becoming proficient in Python is likely to be a good first step.
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