Facebook's Volatile Year in One Giant Chart
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Facebook’s Volatile Year in One Giant Chart

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Facebook's Volatile Year Explained in One Chart

Facebook’s Volatile Year in One Giant Chart

View the high resolution version of today’s graphic by clicking here.

Facebook has found itself in the headlines a lot in 2018, but not for reasons investors are likely to be excited about.

The tech giant battled privacy scandals, policy changes, and dwindling user engagement throughout the year, and in July the company made history with an overnight drop of $119 billion in market capitalization – the single largest drop in U.S. history.

We did today’s chart in conjunction with Extraordinary Future 2018, a tech conference featuring Cambridge Analytica whistleblower Christopher Wylie as a speaker on Sep 19-20 in Vancouver, BC, to show Facebook’s volatile year in perspective.

Here is a recap of some of the more major events that prompted volatility so far in 2018:

Zuckerberg Sells Shares

Facebook CEO Mark Zuckerberg drew attention in September 2017 when he announced plans to systematically sell off up to $12 billion in stock – nearly 50% of his personal stake.

It’s all part of a plan to transfer the bulk of his stake to the Chan-Zuckerberg Initiative. Zuckerberg and his wife Priscilla Chan founded the philanthropic company at the end of 2015 with the stated focus of “personalized learning, curing disease, connecting people and building strong communities.”

Zuckerberg started unloading stock with an initial sale of 1.14 million shares in February 2018 – the biggest insider sale of shares of any public company in the preceding three months. While analysts didn’t see any red flags for the sale at the time, the volume came when the share price needed all the stability it could get.

Facebook’s Privacy Scandal

On March 16, The Guardian and The New York Times published joint exposés reporting that 50 million Facebook user profiles were harvested by Cambridge Analytica without user knowledge. Later estimates pegged that number at closer to 87 million profiles.

Facebook soon found itself the focus of an investigation from the Federal Trade Commission, and published full-page ads in British and American newspapers to apologize for a “breach of trust”. As Facebook scrambled to regain user trust, share values dropped by 17.8% over the 10 days after the scandal broke.

In April, Zuckerberg appeared before Senate to answer tough questions about Facebook’s privacy policies. The CEO’s testimony restored some faith in the stock, and it gained some traction over the next three months, but the damage was already done.

Facebook’s History-Making Stock Drop

Facebook posted disappointing Q2 results on July 24, attributing their sluggish quarter to dropping user numbers and continued privacy challenges driven by General Data Protection Regulation (GDPR) deadlines.

The report triggered an overnight stock drop of 19% – the single biggest one-day value loss ($119 billion) in U.S. stock market history.

As a result of the rout, Zuckerberg’s personal fortune dropped by nearly $16 billion, an amount that exceeds the total market cap of companies like Dropbox or Snapchat.

Where to from here?

Is this the end for Facebook? The halo may have slipped from the social media golden child, but the company may not be in danger quite yet.

The company’s namesake social network is not the only sandbox it plays in, and the company’s diversity is just the thing that might keep Facebook afloat amidst changing social media sentiment.

Facebook’s purchases of Instagram and WhatsApp are paying off, as those platforms continue to grow steadily. Meanwhile, the investment in Oculus Go could be a game-changer for VR, bringing standalone virtual reality systems to the home market. Finally, Facebook is leveraging its main social network as a place to fine tune algorithms and pave the way for new developments in artificial intelligence and machine learning.

Despite Facebook’s challenges in the realm of social media this year, its expansion into other emerging technologies might help the company secure its future.

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Infographic: Generative AI Explained by AI

What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.

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Generative AI Explained by AI

After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.

We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.

Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.

Without further ado, generative AI as explained by generative AI.

Generative AI: An Introduction

Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.

Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.

Generative AI has a wide range of applications, including:

  • Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
  • Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
  • Audio: Generative AI can generate new music tracks, sound effects, and even voice acting

Disrupting Industries

People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.

Generative AI has the potential to disrupt several industries, including:

  • Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
  • Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
  • Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences

Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.

In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.

How This Article Was Created

This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.

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