On Hive: We Can Build Tens of MIllion In Value

When we look at the numbers, it is simply mind blowing.

Web3 is very powerful. It is also overlooked in terms of what can be generated. My view is most people overlook the fact that we have the ability to generate the value ourselves. There is no outside dependence.

Unfortunately, this falls on deaf ears since most are still focused upon users. This is an approach that has failed repeated due to the fact services are not being offered. At the same time, information is lacking. Here is where we have the ability to radically alter the future of any network.

In other words, we build it ourselves.

That said, there is a reason to do this. We are looking at billion in potential value. Here is where we see the simple art of building can pay enormous dividends over time.

Let us take a look at some of the numbers.

Training Data

By now, all of us have heard about chatbots and the wave of large language models. This is the most recent wave of artificial intelligence that is sweeping the world of technology.

One thing that is constant is the fact that a lot of data is required. This is fed into the neural networks, training the models. Here is where the mega-technology companies have a huge advantage. Google, Twitter, and Facebook are on firm ground simply because of the amount of data they have at their disposal.

The social media companies are also benefiting from the fact much of the data is regular language. This is what allows the machines to learn how humans interact.

Of course, this gives then enormous power. It is not a mistake that the chatbots we see are from some of the largest technology entities in the world. OpenAI is one that is not in this realm yet they were are the forefront of this move.

It is important to mention the NY Times is suing this organization for copyright infringement. Whether this will be effective shows the path OpenAI took. They had to scrape the information off other websites since it lacked its own data.

Here is the key when dealing with artificial intelligence. Data is a large piece of the puzzle. It is also extremely valuable.

Basically, we are talking about millions of dollars.

The Information reports that OpenAI offers between $1 million and $5 million a year to license copyrighted news articles to train its AI models. That’s one of the first indications of how much AI companies plan to pay for licensed material. It sits alongside a recent report saying Apple is looking to partner with media companies to use content for AI training and is offering at least $50 million over a multiyear period for data. The Verge reached out to OpenAI for comment on the numbers

The numbers appear roughly similar to some earlier non-AI licensing deals. When Meta launched the Facebook News tab — since discontinued in Europe — it allegedly offered up to $3 million a year to license news stories, headlines, and previews. But it’s not clear whether the total payouts would equal some of the bigger numbers we’ve seen. Google announced in 2020 that it would invest $1 billion in total to partner with news organizations, for instance. Under pressure from a new law, Google also recently agreed to pay Canadian publishers a total of $100 million annually in exchange for linking to their articles.

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This is not surprising considering what is at stake. The chatbot race is just one section of the AI battle being waged by corporations (and even governments). This is not going to slow down anytime soon.

It should be obvious the challenge that is facing everyone. As these companies get more data, their power grows. It is more difficult for the smaller entities to participate. Just look at the numbers and work out how a start up could pay that. The reality is it cannot.

Here is where a public network like Hive can step in.

Databases Have Value

When considering the potential of something such as LeoGlossary, I am struck by how much these valuations come it at.

If we consider that Hive has a market capitalization of around $130 million, let us look at some numbers.

Let us look at the top banana, Wikipedia.

This is naturally just an estimate, with no clue how much it is truly worth. We have to consider the market cap of the other entities listed there, although certainly not exact comparisons. Meta is close to a trillion dollars market capitalization while Google comes in at over that.

If we tangent to a much smaller site, we do have some sales figured.

Investopedia also is a bit dated in terms of the numbers we have but this is what, ironically, Wikipedia, say:

In August 2010, Forbes sold Investopedia to ValueClick for $42 million. By then, the site had grown to more than 30,000 pieces of content and reached 2.2 million unique visitors per month.[7][8][9] In 2013, ValueClick would then sell Investopedia and a group of other properties to IAC for $80 million.[10]

Source

Again, we can presume that the numbers today are a bit higher than given here. Certainly, it is safe to conclude that Investopedia is worth well over $100M, perhaps pushing the $200M total.

Whatever the exact number, this is, at a minimum, in the range of the totality of Hive. We have to fully embrace how valuable data is.

Web3 Data

Simply by building up a database, Web3 networks can enhance their value. This means moving away from Web 2.0. I firmly believe Web3 will not be successful if it is depending upon Web 2.0 data.

There are many reasons why people should focus their attention on these databases. As mentioned earlier, we need to generate data that any organization can use. Feeding the traditional animals is only going to enhance the power of people like Musk and Zuckerberg. This is not the best option for the future.

Another reason is monetization. The internet requires data. Every front end (website) is tied to back end infrastructure. A part of this are databases build which are fed into the websites. We know this is a Web 2.0 world, something that has to be addressed.

With public blockchains, anyone is free to write to the database. This is very powerful. We know from the social media entities how they can negate this ability in an instant.

That is not the case with Web3.

Now we have the ability to switch the focus from the nonsense of pumps and dumps. Instead of living as "green candle people", the industry can start focusing upon building. This is crucial going forward. When we look at the history of the largest technology companies, they spend years building.

We are seeing the fruits of those efforts. Obviously, they have a large number of users. However, and more importantly, they have an enormous amount of data.

Web3 networks can enhance their value simply by increasing the amount (and type) of data they house. Here is where stake holders can actually influence the value of what they have.

We see the numbers. There is a tens of millions in value out there. To start affecting Web 2.0, we have to start the data race. This will not be won by feeding them more.

If you want a network worth a billion dollars, simply build a database with that value.

It is pretty straightforward.

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