Internet vs AI: How To Compare?

Are there parallels to be found between the current state of artificial intelligence and development of internet several decades ago. Are both comparable?


My top 3 lessons* on internet-era experiences and artificial intelligence from Marc Andreessen and Ben Horowitz

This is a natural human trait that we want to compare anything new with something that has already happened in the past. For example, when speaking about AI we refer back to and draw parallels with the early days of the internet. But can these two be compared?

Both, Marc Andreessen and Ben Horowitz, were right in the middle of things when the internet was taking off and they lived through the spectacular burst of the bubble in 2001. Now they are putting their own and their investors’ money into the new generation of AI startups. It is hard to imagine anyone better placed to evaluate and to compare both.

Here are my 3 takeaways from watching another conversation between Marc and Ben on YouTube:

Lesson #1

The Internet was built as a network. It benefited from the network effects. This reminds us of Metcalfe’s law – that the value of a network is proportional to the square of the number of connected users or devices in the network. 

While AI may have some network effects it is essentially a new information processing system, a computer. Comparison with the early days of microprocessors and the computer industry could be more appropriate because networks evolve differently than computers.

The debate about how many large language models are here to stay triggers a memory that one of the bosses at IBM at the time was quoted saying that having 5 computers is all the world needs. And he was right because he was talking about the mainframes. It just happened years before the first personal computers appeared.

Lesson #2

The value of data might be something that is overrated today. The often-heard saying that “data is the new oil” is just a new cliche. There is no marketplace for data.

This doesn’t mean, of course, that data has no value at all. There are exceptions –  the cases when data is super-highly structured, it is of general purpose and not widely available. 

Every company has data that could be used to improve its business. But almost no company has data that it could sell. 

Lesson #3

One of the early internet-era lessons that might have relevance today is the boom-and-bust nature of it. Far too many startups got funded and went out of business. Money got poured into creating the network infrastructure which resulted in excess capacity of optical fibre networks. It took years to put this to proper use.

We may not need that many AI companies or that quantity of chips. There may be too many data centres currently being built or planned. The most dangerous words in the business and investment world are – “This time it’s different!”

And, as a final note, a small reminder from Ben. For some reason we are used to invoking comparisons with gold rushes only when we want to emphasise the negatives. However, some people made money during the gold rush. And some of them even found gold.

For those willing to try and pick top lessons of their own here is the link.

* from anything that you are reading, watching or hearing you can realistically expect to remember a limited number of things only. My solution is to pick just 3 items or ideas from any material. This number is non-negotiable. Even the most extraordinary experience gets compressed into 3 things to remember. This approach has worked for me so far.

This note was first published on Medium.com on 18 October 2024