How Long it Took for Popular Apps to Reach 100 Million Users

Of Twitter’s many new rivals, Meta’s newest social media platform Threads has established its presence with a bang.

According to Meta founder Mark Zuckerberg, Threads took only 5 days to reach the key threshold of 100 million users. It achieved this milestone through organic demand—and no paid promotions required—smashing all previous records.

But how long have other popular platforms—TikTok, Instagram, and YouTube to name a few—taken to build their user base? Pulling data from PwC and Yahoo, we rank how long it took popular platforms to get to 100 million users.

Ranking Every Apps Journey to 100 Million Users

In first place, Threads has a significant lead over the rest of the pack with its five day achievement, and may have built a significant moat in holding on to this record.

Firstly, its launch coincided with Twitter’s viewing limit decision, and rode the wave of dissatisfaction aimed at Twitter’s current owner, Elon Musk.

Secondly, new users on Threads need an Instagram account to register, thus eliminating sign-up barriers and leveraging Instagram’s 1.2 billion-strong user base.

Here’s the journey length of popular platforms to attaining 100 million users:

Ranked second, Open AI’s ChatGPT launched in November 2022 and hit 100 million users by the start of the new year. ChatGPT introduced the incredible capabilities of large language models to the masses, prompting a rush of sign-ups, and reviving old conversations around the potential consequences of AI.

Coming in at third place, ByteDance’s TikTok took just 9 months to reach 100 million users after its launch in 2017. Like Threads, TikTok benefited from another app, accessing popular lip syncing app Musical.ly’s existing user base after it was acquired and folded into TikTok.

WeChat and Instagram round out the top-five, also with interesting advantages. WeChat, an instant messaging platform similar to WhatsApp, benefited from its unique access to China’s notoriously closed internet market of 500 million users in 2012.

Meanwhile, Meta acquired Instagram when the photo-sharing platform had 30 million users, and more than tripled that number past 100 million in just one year.

And while Facebook ranks solidly middle-of-the-pack for fastest to 100 million users, it remains the platform with the most monthly active accounts, at nearly 3 billion. In fact, Meta’s lessons learned from Facebook have been well-leveraged, and the company owns 4 of the fastest apps to register 100 million users.

So What Does Threads Success Mean for Twitter?

Coming back to Threads’ incredible feat, however, it’s still early days whether an en-masse switch from Twitter is on the cards for Meta’s newest platform.

For one, Threads has faced significant criticism due to its intensive data collection practices and lack of accessibility features. It also is missing some key features from its rival, including trending topics, hashtags, and direct messages.

Meanwhile Elon Musk has been less than pleased with Threads’ success, deeming it a copy of Twitter and even threatening legal action.

Competition is fine, cheating is not

— Elon Musk (@elonmusk) July 6, 2023

So where does this leave the increasingly-crowded social media space? The next decade will set the stage for either more platform consolidation, or even further audience fragmentation.

The post How Long it Took for Popular Apps to Reach 100 Million Users appeared first on Visual Capitalist.

Published

7 days ago

on

July 12, 2023

By

Alan Kennedy

Graphics & Design

• Sabrina Fortin

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The following content is sponsored by Lloyd's Register Foundation

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Global Sentiment on AI

Artificial intelligence (AI) has become a revolutionary force with the potential to transform many aspects of our daily lives. So understanding how the average person feels about this technology is essential as it integrates further into society. 

In this graphic sponsored by Lloyd’s Register Foundation, we explore the findings of the World Risk Poll 2021: A Digital World.  

The World’s Opinion is Divided

In the poll, which had 125,000 respondents in 121 countries, people were asked if AI would ‘mostly help’ or it would ‘mostly hurt‘ people in their home country over the next 20 years.

We’ve looked at the ratio of these responses below.

A higher ratio above 1.0 indicates that more people think AI could ‘mostly help’, while a ratio below 1.0 suggests that the population has more skepticism towards the technology.

Globally, the average ratio is 1.4, but significant differences can be seen when looking at each individual region.

Region	Ratio
East Asia	4.4
Northern/Western Europe	1.8
Australia and New Zealand	1.7
Eastern Europe	1.4
Southern Europe	1.3
Central Asia	1.2
South East Asia	1.2
Middle East	1.0
North America	1.0
Latin America & Caribbean	0.9
South Asia	0.9
Central/Western Africa	0.8
North Africa	0.7
Southern Africa	0.6
Eastern Africa	0.4

Notably, public opinion among the biggest economies appears split.

When we dug into the data, we saw that the U.S. showed skepticism towards AI with a ratio of 0.9. In this case, the potential loss of jobs could possibly be the leading cause of apprehension.

On the other hand, China expressed a ratio of 4.5, meaning for every 1 respondent that believes AI will ‘mostly harm’, 4.5 said AI would ‘mostly help’.

Why is AI So Polarizing? 

AI has always been a divisive subject, and even the media can’t settle on whether AI is akin to the chaotic and malevolent Ultron or the caring and cat-obsessed Lt. Cmdr Data.

Consequently, it’s not just a person’s nationality or media consumption that impacts their stance on AI. A person’s life experience may also play a role in their perception of AI, more notably when it comes to religious views or access to the internet:

View	Refused/Don't Know (%)	Neither (%)	Don’t Have Opinion (%)	Mostly Harm (%)	Mostly Help (%)
Has Access to the Internet	5%	3%	22%	26%	44%
Do Not Have Access to the Internet	15%	2%	23%	32%	28%
Religion is Important	9%	1%	24%	34%	32%
Religion is Not Important	7%	4%	20%	21%	48%
Has Experienced Discrimination	6%	3%	21%	35%	35%
Has Not Experienced Discrimination	9%	2%	24%	32%	33%

Artificial intelligence has many philosophical ramifications, so it’s no surprise that only 32% of those who consider religion important believe AI will help. Conversely, 48% of non-religious people believe AI will ‘mostly help’.

In 16 countries, the percentage of people who say AI will ‘mostly harm’ was higher among those who had experienced discrimination based on their race/nationality, skin color, or sex, compared to those who had not. Notably, these include three Northern European countries where overall perceptions of AI are among the most positive in the world: Norway, Denmark, and Sweden.

An Uncertain Future

Even though 39% of global respondents believe AI will ‘mostly help’ in the next 20 years, only 27% of those people believe they would feel comfortable behind the wheel of a self-driving car. This suggests that while people may be ready for AI as a tool, they may not be ready for it to control large parts of their life.

With this in mind, understanding public opinion is crucial for policymakers and industry leaders to then shape the development and deployment of AI technologies in a manner that addresses these concerns. 

Lloyd’s Register Foundation has created the World Risk Poll 2021 to help engineer a safer world, but the scope of this study goes beyond AI and personal data. In part two of this series, we’ll explore the World Risk Poll 2021: Safe At Work and unearth some startling trends regarding workplace harassment. 

Learn more about the risks faced by ordinary people around the globe. Download the free report here.

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Related Topics: #World Risk Poll 2021 #china #artificial intelligence #world #global #ai #public opinion #U.S. #lloyds register foundation #LRF

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The post Mapped: Global Sentiment on AI appeared first on Visual Capitalist.

Is generative AI the catalyst for the next industrial revolution? Or is it a flash in the pan? Is the entire workforce destined to become AI makers and managers?

It’s possible that one, all, or none of these options could be correct. But despite how fast large language models (LLMs) and tools have grown the popularity of artificial intelligence, one thing that is clear is that there are no quick or easy answers.

Amidst all this uncertainty, opinions on how we use AI in the workplace have evolved. Recent survey data from Boston Consulting Group (BCG) reveals how the labor force feels about AI in the workplace today, compared to how they felt five years ago.

The consultancy surveyed 13,000 people (C-suite leaders, managers, and frontline employees) in 18 different countries for the results, and divided their top two responses into five categories: Curiosity, Optimism, Concern, Confidence, and Indifference.

Data note: Since the top two feelings were selected and categorized per question, the percentages across categories do not total to 100%.

More Optimism, Less Caution Around AI

General curiosity about AI remains almost unchanged (at 60%) since 2018.

Meanwhile, despite how rapidly AI has advanced in the last five years, or perhaps because of it, more than 50% of workers surveyed are optimistic about AI’s impact on work, a 17 percentage point (p.p.) increase from 2018.

And though 30% remain concerned about AI, this fell 10 p.p. over the same time period.

Sentiment towards AI	2018	2023
Curiosity	60%	61%
Optimism	35%	52%
Concern	40%	30%
Confidence	17%	26%
Indifference	21%	14%

Clearly, respondents perceive AI in the workplace far more positively now than they did in 2018. But that’s not all. The respondents’ confidence in how AI can influence their work has also increased (+5 p.p.) and indifference towards it has shrunk significantly (-7 p.p.).

Given the explosive growth in generative AI since the end of 2022—ChatGPT gets 1.8 billion visitors a month—it’s not surprising that workers are far more aware of AI compared to just five years ago.

Optimistic Leaders, Cautious Employees

As with any survey data, the devil is in the details. BCG notes that the sentiments between rungs on the company ladder differ sharply around AI.

While two-thirds of polled leaders are optimistic about AI in 2023, less than half of polled frontline employees shared the same sentiment. Frontline employees were also the biggest group that responded with concern (nearly 40%).

Importantly, frontline employees are almost as optimistic as they are concerned about AI in the workplace.

Position	Optimism	Concern
Leaders	62%	22%
Managers	54%	28%
Frontline Employees	42%	39%

Managers were closer to leaders in their AI optimism, though some experts believe their jobs might actually be the most at risk of being replaced all together.

More Use, More Optimism Around AI

With ChatGPT reaching 100 million active users just two months after launching, it’s clear that more and more people are experimenting with generative AI.

In BCG’s poll, regular AI users—categorized as people who use it at least once a week for work—are nearly three times more optimistic than concerned about AI’s impact on their work in 2023.

AI Use Level	Optimism	Concern
Regular	62%	22%
Rare	55%	27%
None	36%	42%

Even rare users are two times more optimistic than cautious, with the non-user category registering the most concern.

Which brings us to who these regular users are.

A staggering 80% of the leaders polled say they’re already regular users of AI, compared to 46% managers and 20% frontline employees.

While eyebrow-raising, these figures are not surprising.

People in leadership positions tend to have a mandate to stay ahead of the curve on current business trends, and along with their less strictly defined roles, have more freedom to try, use, and adopt AI tools while they formulate policies for their workplace.

Position	Regular User	Rare User	Nonuser
Leaders	80%	12%	8%
Managers	46%	23%	31%
Frontline Employees	20%	20%	60%

At the same time, AI tools may not be green-lit en masse in many workplaces yet, preventing frontline employees from giving them a go.

So Is AI Coming For Jobs or Not?

Regardless of how definitively one can make a claim about artificial intelligence taking away people’s jobs, the survey respondents were unanimous that AI in the workplace will have some kind of an impact on their employment.

Slightly more than one-third felt that their job is in jeopardy as of 2023, while an overwhelming 86% polled said they needed training to adapt to how AI will transform their work.

With how fast the field is currently transforming, upskilling could be the safest path to follow as the AI revolution unfolds.

The post Charted: Changing Sentiments Towards AI in the Workplace appeared first on Visual Capitalist.

Meet the Competing Apps Battling for Twitter’s Market Share

The Twitterverse is under siege as a flurry of microblogging platforms, keen to capitalize on simmering discontent, vie for its vast user base. Among the most serious contenders are five apps offering diverse solutions, each with their unique appeal.

Five Twitter Alternatives

At the top of the list is Meta’s Threads, a fresh entrant that leverages the success and massive userbase of Instagram. Launched hot on the heels of Twitter’s controversial ‘rate limit’ decision in June 2023, Threads emulates Twitter’s microblogging approach with an Instagram twist. The new kid on the block swiftly amassed over 30 million users on its launch day, posing a credible threat to Twitter’s dominance.

Meanwhile, the decentralized platform Mastodon, which has been running since 2016, continues to challenge the status quo. Its open-source model enables user control over data and privacy, providing an alternative to mainstream social media monopolies. Mastodon saw a big surge in users last year as Elon Musk took control of Twitter—a move that was wildly unpopular with a subset of users.

Another decentralized contender is BlueSky, a brainchild of Twitter co-founder Jack Dorsey. Still in its nascent ‘invite-only’ stage, BlueSky already has a whopping 1.2 million potential users on its waitlist, a testament to its potential to disrupt the social media landscape.

Spill, co-founded by former Twitter employees, is also shaking things up. The platform aims to foster diverse communities rather than mimic Twitter, but the similarities are hard to overlook. Impressively, even though Spill is still invite-only, it has become one of the most downloaded apps on Apple’s App Store.

Lastly, there’s Truth Social, a product of Trump Media & Technology Group. It bills itself as a bastion of free speech. In the aftermath of Twitter’s introduction of a daily post limit by Elon Musk, Truth Social’s servers were overwhelmed by an influx of users seeking an unrestricted social media experience.

As these platforms fight for Twitter’s turf, only time will tell who’ll come out on top. Twitter’s rule remains challenged, but the battle for social media supremacy is far from over.

The post Meet the Competing Apps Battling for Twitter’s Market Share appeared first on Visual Capitalist.

Published

2 weeks ago

on

July 5, 2023

By

Marcus Lu

Graphics & Design

• Zack Aboulazm

Industrial Automation: Who Leads the Robot Race?

The advent of industrial robotics has triggered a wave of automation that is progressively sweeping across global industries. Countries that deploy these robots in great numbers are likely to increase their productivity and lower their costs of production.

With this in mind, the graphic above from our sponsor MSCI ranks the top countries by industrial robot installations.

Data and Highlights

This data was sourced from a 2022 report published by the International Federation of Robotics.

Country	2012	2015	2018	2021
China	23,000	69,000	115,000	268,000
Japan	29,000	35,000	55,000	47,000
U.S.	22,000	28,000	40,000	35,000
South Korea	19,000	38,000	38,000	31,000
Germany	18,000	20,000	27,000	24,000
Rest of World	48,000	64,000	108,000	112,000

It may not be surprising that China leads the world in industrial automation, given its prowess in mass production. In fact, in 2021, China installed more industrial robots than all other countries in the world combined.

According to the IFR report, 56% of the robots that China installed in 2021 were deployed in automotive or electronics-related industries. The same trend can be seen in Japan, with 53% of its 2021 installations also being in those two industries. 

America’s installations were more evenly distributed, with 36% dedicated to automotive and electronics. Other major sectors were metals and machinery (11%), plastics and chemicals (10%), and food (10%). 

Robotics for the Future

Falling birth rates and the aging of the baby boomer generation suggest that many of the world’s biggest economies will eventually experience labor shortages. This is evidenced by the constrictive population pyramids of Japan, the U.S., Europe, and even China. 

The IFR believes that robotics can help to solve this problem, not just in manufacturing, but also in critical industries like agriculture and healthcare. 

For example, robotics are expected to become more common in the surgery room, where they can perform intricate procedures with the help of artificial intelligence. The market for surgical robots is expected to reach over $20 billion by 2030, up from $4.4 billion in 2020.

Given the vast array of use cases, robotics and AI are two technologies that could rapidly transform our world over the coming decades. Investors can gain insight with the MSCI ACWI IMI Robotics & AI Index, which benchmarks an investable universe of companies associated with automation.

Explore the MSCI ACWI IMI Robotics & AI Index now

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Related Topics: #technology #innovation #industrial robotics #business #artificial intelligence #robots #automation #disruption #msci

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Published

3 weeks ago

on

June 30, 2023

By

Tessa Di Grandi

Graphics & Design

• Sabrina Fortin

What is a Digital Goldmine?

Gold has played a pivotal role in the global economy for thousands of years, and even after the abandonment of the gold standard, the yellow metal has remained an important part of many investment portfolios.

Today, whether in the form of bars, coins, ETFs, or digital tokens, gold’s enduring value continues to make it an attractive asset. However, mining a physical metal also comes with significant environmental costs.

In this graphic, our sponsor Nature’s Vault looks at the impact of gold mining and demonstrates how adding gold-linked assets to your portfolio can be an environmentally friendly alternative.

The Environmental Cost of Gold Mining

To start, gold mining’s environmental implications include deforestation, waste production, and carbon emissions.

The expansion of gold mines from 2000 to 2019 led to over 3,500 km² of deforestation. In addition, annual emissions are estimated to be around 126 million CO²e tonnes.

What’s more, approximately 99% of the ore extracted from gold mining goes to waste. Tailings, the main waste generated from gold extraction, contain high levels of heavy metals. When exposed to water or wind, these metals can leach into the surrounding environment, posing a variety of health risks and inflicting long-term harm on ecosystems.

After extraction, processing, and refinement, physical gold used as assets are stored away in vaults, raising the question: is the environmental cost justified?

The Solution: A Digital Goldmine

Investors can now add a gold-linked asset to their portfolio without the environmental toll.

Nature’s Vault is decarbonizing the gold mining sector by creating digital assets like the NaturesGold Token and the Pistol Lake NFT that monetize the preservation of gold in the ground. As a result, the emissions and the environmental damage associated with mining are avoided.

So, how does a digital goldmine work exactly?

1. Nature’s Vault identifies and evaluates mining rights with independently quantified gold deposits.
2. They then acquire and maintain unencumbered legal titles to these mining rights to prevent the sale or exploitation of the underlying gold deposits.
3. Finally, gold-linked assets are created by tokenizing mineral rights and preserving in-ground gold using blockchain and asset fractionalization.

This way, gold for investment can still be used without the associated damage of mining.

Learn more about gold-linked assets from Nature’s Vault.

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Related Topics: #green invest #token #digitization #tokenization #Nature's Vault #gold mining

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Published

3 weeks ago

on

June 27, 2023

By

Marcus Lu

Graphics & Design

• Sabrina Lam

Ranking Industries by Their Potential for AI Automation

Since the release of tools like ChatGPT, artificial intelligence (AI) has begun to permeate industries worldwide, transforming the way we work and live.

To gain insight into this rapidly evolving landscape, our sponsor MSCI has ranked U.S. industries by their estimated share of employment that could be exposed to AI-driven automation.

Data and Highlights

This analysis comes from a March 2023 report published by Goldman Sachs Global Investment Research. 

The authors estimated automation exposure for over 900 U.S. jobs using the O*NET occupational database, which provides details on the types of tasks each occupation conducts. Exposure estimates were then weighted by the employment share of each occupation, and aggregated to the industry level. 

Industry	Estimated Share of U.S. Employment Exposed to AI (%)
Office and administrative support	46%
Legal	44%
Architecture and engineering	37%
Life, physical, and social science	36%
Business and financial operations	35%
Community and social service	33%
Management	32%
Sales and related	31%
Computer and Mathematical	29%
Farming, fishing, and forestry	28%
Protective service	28%
Healthcare practitioners and technical	28%
Educational instruction and library	27%
Healthcare support	26%
Arts, design, entertainment, sports, and media	26%
All industries average	25%
Personal care and service	19%
Food preparation and serving related	12%
Transportation and material moving	11%
Production	9%
Construction and extraction	6%
Installation, maintenance, and repair	4%
Building and grounds cleaning and maintenance	1%

According to these findings, “office and administrative support” will likely be the most affected by AI-driven automation at 46%. This transformation could largely impact common tasks such as data entry, scheduling meetings, and document management.

The second highest industry, “legal”, trails close behind at 44%. AI is expected to automate legal processes like contract analysis, and could even be used to anticipate court case outcomes.

As expected, industries that won’t be heavily impacted are those that rely heavily on manual labor, like “construction and extraction.” 

Benchmarking the Automated Future

AI is still a very new and developing technology. How it will impact labor productivity in the future depends on its capability (how fast it improves) and adoption (how quickly people and businesses begin using it). 

Adoption rates are unlikely to be the same around the world, as survey results have shown that some countries are more optimistic towards AI than others.

Under the most aggressive scenario, Goldman Sachs believes that AI automation could impact up to 300 million jobs globally and potentially result in a 7% increase in annual GDP (equal to about $7 trillion). 

Given AI’s massive potential for disruption, it’s more important than ever for investors to stay ahead. That’s why MSCI has created the MSCI ACWI IMI Robotics & AI Index, which benchmarks an investable universe of companies associated with the adoption of AI, robotics, and automation.

Explore the MSCI ACWI IMI Robotics & AI Index now

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Charted: Companies in the Nasdaq 100, by Weight

Launched in 1985, the Nasdaq 100 index tracks the performance of the largest, and most actively-traded, non-financial companies listed on the Nasdaq stock exchange.

The index is capitalization-weighted, meaning that stock weights in the index are based on each company’s market cap (with some rules to rebalance if companies have an oversized influence). For example, leaders Apple and Microsoft amounted to more than one-fourth of the Nasdaq 100’s total market capitalization alone as of April 2023.

One of the most well-known trackers of the index, Invesco QQQ’s ETF, is the data source for today’s visualization by Truman Du.

Just 7 Companies Dominate the Nasdaq 100

Microsoft and Apple, together with the next five ranked companies, made up over 50% of the total weight of the index in April. These companies are: Alphabet (Google), Amazon, NVIDIA, Meta, and Tesla, with Alphabet’s class A and class C shares occupying two spots.

Here’s a breakdown of all 100 companies on the Nasdaq 100, by percentage weight in the index on April 19, 2023.

Company	Allocation
Microsoft	12.63%
Apple	12.60%
Amazon	6.31%
NVIDIA	5.29%
Alphabet (Class A)	3.74%
Alphabet (Class C)	3.70%
Meta (Class A)	3.68%
Tesla	3.38%
Broadcom	2.03%
PepsiCo	1.95%
Costco	1.69%
Cisco	1.51%
T-Mobile	1.39%
Adobe	1.33%
Comcast (Class A)	1.23%
Texas Instruments	1.23%
AMD	1.11%
Netflix	1.10%
Qualcomm	1.01%
Honeywell International	1.01%
Amgen	1.01%
Intel	0.99%
Intuit	0.96%
Starbucks	0.94%
Gilead Sciences	0.80%
Intuitive Surgical	0.80%
Booking Holdings	0.77%
Mondelez International (Class A)	0.74%
Analog Devices	0.73%
Applied Materials	0.71%
Automatic Data Processing	0.69%
Regeneron Pharmaceuticals	0.67%
PayPal Holdings	0.65%
Vertex Pharmaceuticals	0.65%
Fiserv	0.56%
Activision Blizzard	0.51%
Lam Research	0.51%
Micron Technology	0.51%
MercadoLibre	0.50%
CSX Corp	0.48%
Palo Alto Networks	0.45%
Cadence Design	0.45%
Synopsys	0.44%
O'Reilly Automotive	0.43%
Moderna	0.42%
ASML Holding NV ADR	0.42%
Monster Beverage	0.42%
Marriott (Class A)	0.41%
Fortinet	0.40%
Charter Communications (Class A)	0.40%
KLA Corp	0.38%
Keurig Dr Pepper	0.38%
Airbnb (Class A)	0.38%
Kraft Heinz	0.37%
American Electric Power	0.37%
DexCom	0.37%
Cintas Corp	0.35%
Lululemon	0.35%
AstraZeneca PLC ADR	0.35%
NXP Semiconductors NV	0.34%
Microchip Technology	0.33%
Exelon Corp	0.33%
Autodesk	0.33%
Biogen	0.32%
PDD Holdings Inc ADR	0.32%
IDEXX Laboratories	0.31%
Paychex	0.30%
Workday (Class A)	0.30%
Xcel Energy	0.30%
Seagen	0.29%
PACCAR	0.29%
ODFL	0.29%
Copart	0.29%
Illumina	0.28%
Ross Stores	0.28%
EA	0.27%
Marvell Technology	0.27%
Global Foundries	0.27%
Warner Bros. Discovery (Class A)	0.27%
Dollar Tree	0.25%
Baker Hughes (Class A)	0.24%
Fastenal	0.24%
Cognizant (Class A)	0.24%
Enphase Energy	0.23%
Walgreens Boots	0.23%
Verisk Analytics	0.23%
CrowdStrike Holdings (Class A)	0.22%
CoStar Group	0.22%
Ansys	0.22%
Align Technology	0.21%
Diamondback Energy	0.20%
Constellation Energy	0.19%
Atlassian Corp A	0.19%
eBay	0.18%
Datadog (Class A)	0.16%
JD.com ADR	0.13%
Zoom	0.13%
Sirius XM Holdings	0.12%
Zscaler	0.11%
Lucid Group	0.11%
Rivian (Class A)	0.09%

The dominance of these seven companies within the NASDAQ 100 is a reflection of how central they are to large parts of the wider consumer economy. The economic output and influence of the tech giants speaks for themselves, and Tesla still leads the (rapidly crowding) electric vehicle market.

Perhaps the underdog of the bunch is NVIDIA, which produces graphics processing units (GPUs) that power the visuals in many electronic devices and, more recently, artificial intelligence (AI) systems. The latter in particular has made investors incredibly bullish on the company, as NVIDIA’s stock has risen and the company has recently joined the coveted $1 trillion club.

It’s important to note that this snapshot changes drastically over time. For example, Intel and Cisco were massive components of the Nasdaq 100 in the 2000s but have seen their allocations drop, while others like Yahoo! are no longer publicly traded.

The Pros and Cons of Market Consolidation

Such imbalance in the Nasdaq 100 has both benefits and downsides.

The success of the biggest contingents can pull up the entire index, and the Nasdaq 100 has consistently outperformed broader markets. In fact, $10,000 invested in the Nasdaq 100 in 2013 would be worth $50,000 today, while the same investment in the S&P 500 would now be $30,000.

However, if even one of these large companies underperforms, it can have a major impact on the entire index. This outsized influence can also hide general market woes that may be affecting many other components of the index, and the economy.

With the advent of large language models of AI in 2022, the tech sector is on a precipice. Will AI lead to further profitability—and bigger market caps—or will it render entire companies defunct, leading to a big shakeup in the composition of the Nasdaq 100 index?

The post Charted: Companies in the Nasdaq 100, by Weight appeared first on Visual Capitalist.

The Most Popular Desktop Operating Systems Since 2003

Mobile phones might be the most common way of getting online today, but the digital and internet era started for most people with the humble desktop computer.

And over the past 20 years, a long list of operating systems (OS) have been used to run the most popular desktop computers.

Sjoerd Tilmans has created an animated chart showing the rise and fall in market share of popular desktop operating systems over the period of May 2003 to June 2022, using data from W3Schools and GS Stat Counter.

Microsoft’s Monopoly on the Most Popular Desktop OS

The story of the desktop OS market is a story of Microsoft’s explosive growth and market dominance.

In the 1980s, the fledgling company signed a partnership with personal computer behemoth IBM. Microsoft would supply IBM with an operating system for its computers, MS-DOS, and receive a royalty for every computer sold.

Those royalties boosted Microsoft’s coffers. And its release of Windows—a more visual interface than DOS—helped them grab hold of the PC market. The late 1990s and early 2000s saw different versions of Windows capture the market:

• Windows 95:
  The now famous toolbar and Start menu made their debut here. The version also would launch Internet Explorer, once the world’s most popular browser.
• Windows 98:
  An upgrade to ‘95 which supported more hardware like USBs and connecting more than one monitor.

• Windows XP:
  XP quickly became a fan-favorite because of its stability, and a hit with both commercial and personal computer clients. Windows XP gained market share steadily upon release in 2001, quickly becoming the most popular desktop OS with a peak of 76% market share in 2007.

Operating System	Peak Market Share	Year
Win 95	57.4%	1998
Win 98	17.2%	1999
Win XP	76.1%	2006

Microsoft doubled down on their next releases from the end of the 2000s to 2020, with some misses (Windows Vista) and some hits (Windows 10). Here’s a look at the most popular ones:

• Windows 7:
  Released as the successor to the poorly received Windows Vista, it kept the same visual style (“Aero”) but greatly improved performance and stability from Vista’s benchmarks. In 2011, Windows 7 passed XP to become the most popular desktop OS.
• Windows 8 and 8.1:
  Created for tablet-desktop integration, just as Microsoft released the companion Surface tablet. The beloved Start menu was replaced (an unpopular decision) and tile-based visual style introduced. However the dramatic differences between the desktop and tablet versions made for a steep learning curve, with the 8.1 release reintroducing the Start button.
• Windows 10:
  The follow-up to Windows 8 kept the the tile-based appearance but focused on a desktop-oriented interface with quality of life updates. By 2018, Windows 10 had become the most popular desktop OS, eventually peaking at 61% market share at the start of 2022.

Date	Peak Market Share	Year
Win 7	55.1%	2014
Win 8	8.1%	2013
Win 8.1	16.8%	2015
Win 10	61.2%	2022

The most recent version of Windows released, Windows 11, had updated graphics styling, widget integration, and introduced Microsoft’s latest internet browser Microsoft Edge. But it received a mixed response and slow uptake compared to Windows 10, gaining a market share of 8.3% by June 2022.

Microsoft Vs. Other Desktop OS Contenders

As of February 2023, Microsoft had a comfortable lead in the desktop OS market, holding nearly 72% of the market.

Company	OS Name	Feb, 2023 Market Share
Microsoft	Windows	72.0%
Apple	macOS	16.3%
OpenSource	Linux	2.9%
Google	ChromeOS	2.9%
Unknown	Unknown	6.0%

In a distant second is Apple’s macOS. The most profitable company in the world might make most of their money from smartphones, but Apple has still managed to carve out a small but sturdy segment of the desktop operating OS market. It reached its peak of 19% in April 2020.

The other tech giant in the desktop OS game is Alphabet, whose ChromeOS is unique for using an internet browser (Google Chrome browser) as its primary interface. Generally packaged as a simpler and cheaper device option—it was primarily released with inexpensive laptops called “Chromebooks”. More recently, Alphabet announced a version that can be installed on existing computer hardware in 2022.

Compared to the commercially released OS above, Linux is completely free to download and use, and is the largest open-source software project in the world. Although the OS is only used in about 3% of desktop computers, it was also the basis of Android and ChromeOS, and is the most-used OS on devices with embedded software—routers, smart home devices, cars, and even a few spacecraft (The SpaceX Falcon 9, for example).

The post Animated: Most Popular Desktop Operating Systems Since 2003 appeared first on Visual Capitalist.

Published

4 weeks ago

on

June 21, 2023

By

Chris Dickert

Graphics & Design

• Sabrina Fortin

Artificial Intelligence: The Journey to a Thinking Machine

When the latest iteration of generative artificial intelligence dropped in late 2022, it was clear that something significant had changed.

The language model ChatGPT reached 100 million active monthly users in just two months, making it the fastest-growing consumer application in history. Meanwhile, Goldman Sachs predicted that AI could add 7% to global GDP over a 10-year period, almost $7 trillion, but also replace 300 million jobs in the process.

But even as AI continues to disrupt every aspect of life and work, it’s worth taking a step back. 

In this visualization, the first in a three-part series called The AI Revolution for sponsor VERSES AI, we ask how we got here, where we’re going, and how close are we to achieving a truly thinking machine?

Milestones to Mainstream

The term “artificial Intelligence” was coined by computer scientist John McCarthy in 1955 in a conference proposal. Along with Alan Turing, Marvin Minsky, and many others, he is often referred to as one of the fathers of AI. 

Since then, AI has grown in leaps and bounds. AI has mastered chess, beating Russian grandmaster and former World Chess Champion Garry Kasparov in 1997. In 2016, Google’s AlphaGo beat South Korean Go champion Lee Sedol, 4-1. The nine-year gap in achievements is explained by the complexity of Go, which has 10³⁶⁰ possible moves compared to chess’ paltry 10¹²³ combinations.

DALL-E arrived in 2021 and ChatGPT-4 in early 2023, which brings us to today.

But What is Artificial Intelligence?

There’s a big difference between the Roomba that vacuums your condo and HAL from 2001: Space Odyssey. This is why researchers working in the field have come up with the following ways to classify AI:

AI Category	Definition	Example
Artificial Narrow Intelligence (ANI)	An AI that is good at a particular task at a level equal or better than a human being	Virtual assistants, such as Siri or Alexa
Artificial General Intelligence (AGI)	An AI that can perform any task that a human being can. This is what most of us think of when we think of AI	Marvel’s J.A.R.V.I.S. (Just A Rather Very Intelligent System)
Artificial Super Intelligence (ASI)	An AI that can surpass anything that human beings can do	The Minds from Iain M. Banks' sci-fi Culture series

Despite a false alarm by one Google software engineer in 2022 and a paper by early GPT-4 boosters, no one really believes that recent generative AIs qualify as thinking machines, however you define it. ChatGPT, for all its capabilities, is still just a souped-up version of autocomplete. 

Do Androids Dream of Electric Sheep?

That was the title of Philip K. Dick’s science fiction classic and basis for the movie Blade Runner. In it, Harrison Ford plays a blade runner, a kind of private investigator who used a version of the Turing Test to ferret out life-like androids. But we’re not Harrison Ford and this isn’t science fiction, so how could we tell?

People working in the field have proposed various tests over the years. Cognitive scientist Ben Goertzel thought that if an AI could enroll in college, do the coursework and graduate, then it would pass. Steve Wozniak, co-founder of Apple, suggested that if an AI could enter a strange house, find the kitchen, and then make a cup of coffee, then it would meet the threshold. 

A common thread that runs through many of them, however, is the ability to perform at one thing that humans do without effort: generalize, adapt, and problem solve. And this is something that AI has traditionally struggled at, even as it continues to excel on other tasks. 

Can Current State-of-Art AI Achieve Thinking Machines?

And it may be that the current approach, which has shown incredible results, is running out of road.

Researchers have created thousands of benchmarks to test the performance of AI models on a range of human tasks, from image classification to natural language inference. According to Stanford University’s AI Index, AI scores on standard benchmarks have begun to plateau, with median improvement in 2022 limited to just 4%.

New comprehensive benchmark suites have begun to appear in response, like BIG-Bench and HELM, but will these share the same fate as their predecessors? Quickly surpassed, but still no closer to an AI like J.A.R.V.I.S. that could pass the Wozniak Coffee Test?

Imagine a Smarter World

VERSES AI, a cognitive computing company specializing in next generation AI and the sponsor of this piece, may have an answer.

The company recently released research that shows how to build an AI that can not only think, but also introspect and explain its “thought processes.” Catch the next part of The AI Revolution series to learn more.

Learn more about how VERSES AI is building a smarter world.

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Related Topics: #artificial intelligence #singularity #benchmarks #chatgpt #AI tests #dall-e #Verses #versesai

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The post Artificial Intelligence: The Journey to a Thinking Machine appeared first on Visual Capitalist.