AGI is no longer a big buzzword in Silicon Valley. The unfulfilled expectations will affect the future of artificial intelligence.

Like the idea of a true driverless car or nuclear fusion, artificial general intelligence is not going to happen soon, despite hype in recent years suggesting it is not far away.

Most modern artificial intelligence is a form of deep learning or natural language processing. AI is also used for computer vision. Things have moved fast in the last decade, but it is more about sifting through vast piles of data than building machines that think.

General Artificial Intelligence is about building machines, or more accurately software, that can think in ways that resemble human thinking.

That’s a loose definition, experts argue over exactly what GAI means and doesn’t mean. They don’t even agree on its name: there are many variations in use each with a different, nuanced meaning.

GAI doesn’t necessarily mean sentience. At best it is an early step on the path, but it is possible machine sentience can never be achieved.

As The Next Web reports the financiers behind GAI have gone quiet lately. The story suggests they have lost their appetite for the technology.

Source: The AGI hype train is running out of steam

Scot Herrick reminds his readers to think about money the way businesses do.

He writes:

For business, it’s all about the money. Unfortunately, for too many knowledge workers, it isn’t.

Instead, we are told to love our work. We are told to work extra hours – for no pay. We are told that we should be loyal to companies when companies will lay us off in a cold-blooded minute.

This is sound advice.

We’ve all come across examples of large organisations that make vast profits yet lean on individuals to donate knowledge, time and energy in return for… nothing.

Journalists get this a lot. We are often expected to work ‘for exposure’. In most case the people who ask for this work for organisations that never give anything away.

We’ll put the inverse Robin Hood injustice of taking from the poor and giving to the rich aside for one moment and focus on the important point:

If you don’t value your time and work, nobody else will.

Rewarding knowledge workers

Brainpower: Rewarding knowledge workers is an article adapted from a presentation given by consulting firm Mercer. It looks at the needs and wants of knowledge workers from a managerial point of view. While its conclusion is far from original (bosses need to look after knowledge workers if they want to stay competitive) the core message needs underlining.

“…a pressing question facing companies today is how to sustain and grow this competitive advantage, which is created and housed in the minds of its knowledge workers.”

A key part of getting this right is understanding who counts as a knowledge worker. In the past the cut-off point was often thought to be the college degree. That’s still a minimum requirement, but the real key is people who need to adapt their knowledge to solve problems and innovate rather than follow an established procedure or a script.

In the chart that would be those in the top right quadrant.

Anything below the adapt line could, in theory anyway, be automated.


Modern newspaper style books tell journalists to use among, not amongst.

Unlike many style book rules, this one applies on both sides of the Atlantic as well as in Australia and New Zealand.

While both words are technically correct, amongst is regarded as old-fashioned and may soon be obsolete.

My 40 year old copy of the Oxford Concise Dictionary offers the two words as alternatives.

According to the Oxford Dictionaries web site, no-longer online, among is “chiefly British”. This surprised me.

I checked my own work – almost 30,000 documents – and found I’ve used the word ‘amongst’ about 120 times compared with ‘among’ about 800 times. However, in recent years the ratio is much lower.

The Cambridge dictionary thinks Amongst is “more formal”. Merrian-Webster says people use amongst to sound more educated.