Published on 2024-08-21. Modified on 2024-08-23.

I truly and passionately hate hype. From the fakeness of it to the sheer stupidity it represents, but perhaps most of all, because of the devastating consequence it often results in.

Hype is basically to promote or publicize something extravagantly and the modern hype promoted by "Big Tech" is not much different from medieval charlatans.

Hype begins by some company or industry wanting to earn a profit by some new product or service. Massive propaganda is launched which is then propagated by the media, who's objectivity and investigation procedure is totally sidestepped by yet another desperate craving for profit. Then all of this is followed-up by the majority of the masses, which unfortunately mostly consists of mindless sheeple that easily become dumpfounded by all of this, and as a result, start parroting the hype like lunatics.

Hype is always bad.

Hype hurts investors who end up loosing a lot of money because all the "golden" promises where exaggerated or simply fake.

Hype often hurts the medium to smaller businesses because rather than doing what actually works, procedures are changed and complication is introduced, very often resulting in vendor lock-in, higher financial expenses, less security and poorer end results.

Hype also hurts the individual. People who invest time and money in studying and learning the hyped up technology only to realize, often many years later, that better ways actually exist. This is when the old becomes new again and people discover things for the first time that has been obvious to the previous generations all along.

Often, the price that people end up paying is not only in the loss of time and money, but also in some of the most important valuables, namely privacy and personal freedom.

When hype is driven by big corporations or by governments, it is always bad. The reason is simple. The interest at hand is never the benefit of the people, it's the benefit of the company or ruling elite. It is always an exaggeration or a blatant lie. That is one of the reasons why we must always strive to think independently and avoid being swooped by the media and general opinions of the crowd.

In the world of tech, hype is rife. When a new technology emerges, people get overly enthusiastic and want to apply it everywhere—we've seen it with big data, AI, data science, blockchain, ChatGPT, and so on. I've seen companies hire as many as 70 people to build a product with the goal of following a trend without defining what the product would do or whether clients would want it.

Just a few weeks ago, for example, a company reached out to me looking for advice on how they could use ChatGPT in their accounting software. They said this was because they were trying to raise funding, and investors wouldn't like it if they weren't using ChatGPT for something. I've documented many examples of this phenomenon in the context of AI in my book.

— Dr. Emmanuel Maggiori (computer scientist)

The current AI hype

In technology, AI is currently the new big hype. Before AI, it was "The Cloud", which unfortunately has still not settled, but are now also being interwoven with AI.

The term "Artificial Intelligence" (AI) is grossly misleading as no form or sort of intelligence exists at all. The only reason why this terminology is being used is because it is easier to sell. When most people think of AI they tend to think of something from science fiction.

In my humble opinion, about perhaps 10% of the AI hype is based upon useful facts, which is the relevant tools the technology provides, the rest is exaggerated rubbish.

Still, many companies (mainly in the US, but also elsewhere in the world) are firing people because they have been lead to believe that they can save money by utilizing AI rather than real people. This is a big mistake. While "AI" is certainly useful for a lot of minor tasks when used as tools, this is nothing but careless acts of greedy mismanagement.

AI functions greatly as a "search engine" replacement, but replacing customer and service people with AI is going to hurt the business in the long run. Nobody wants to talk to an AI when they need support. We all HATE that! It is bad enough that when you need service and support you end up talking to someone on the other side of the planet who's using some kind of answer sheet with absolutely no clue on how to really help you.

The least skilled, the least experienced, the least productive people will be the ones recommending AI the most. The people who actually think will be treated as either being stupid or totally backwards.

Last, but not least, a lot of the current AI products represents the biggest and most appalling examples of plagiarizing ever witnessed.

The marketing team in the company I work for is now labeling everything a computer does as "AI powered". Technology that existed decades ago is now suddenly "AI powered" - just because they are jumping on the hype wagon.

It is a real shame that some of the most beneficial tools ever invented, such as computers, modern databases, data centers, etc. exist in an industry that has become so obsessed with hype and trends that it resembles the fashion industry.

Another major problem with this new round of hype is that it is taking place in the middle of a major inflation crisis and it is taking place in a time when we need to conserve resources, energy and water. Yet, if anything, AI is slowly becoming a major drain on both resources, energy and water (for cooling in data centers).

Take a step back, pause and breathe before you fall prey to all the hype. A lot of people is going to loose a lot of money. I can say that with complete conviction because most investments into AI have been made on false promises, promises that AI simply cannot and never will be able to fulfill.

Recommended material

• AI HYPE - Explained by Dr. Emmanuel Maggiori (1 hour 20 min. YouTube video)

  Jesse Wright is joined by Dr. Emmanuel Maggiori, computer scientist and author of the book Smart Until It's Dumb: Why artificial intelligence keeps making epic mistakes (and why the AI bubble will burst), in a thought-provoking conversation about AI and the future of AI.

• The "Modern Day Slaves" Of The AI Tech World (52 min. YouTube video).

  Meet the invisible workforce behind tech giants like Google, Facebook, Amazon, and Uber. These underpaid and disposable workers label images, moderate content, and train AI systems, often earning less than minimum wage. Their work is essential yet remains in the shadows, unacknowledged by the companies that depend on them.

• Decoding AI: A Go Programmer's Perspective (30 min. YouTube video).

  This is a really good talk by Beth Anderson from BBC. It was presented at the newly held UK GopherCon.

  Beth debunks common myths and provides a candid look under the hood to reveal what the technologies are and how they work when we attempt to use them in production systems.

  Beth began her journey in the field of AI in the 90s when she studied Computer Science and Artificial Intelligence, culminating in a Master's thesis focused on machine learning—utilising convolutional neural networks to classify audio waveforms. Beth later joined the BBC's pioneering AI team, Datalab, developing recommendation engines and other tooling within the BBC. Beth is also involved with the BBC's AI&ML community which is focused on the responsible use of AI within the organisation.

• Beyond the Hype: A Realistic Look at Large Language Models (40 min. YouTube video).

  This presentation by Jodie Burchell was recorded at GOTO Amsterdam 2024.

  Jodie Burchell is a data scientist and developer at JetBrains.

  If you've been remotely tuned in to the latest developments in large language models (LLMs), you've likely been inundated with news, ranging from claims that these models will replace numerous white-collar jobs to declarations of sentience and an impending AI apocalypse. At this stage, the hype surrounding these models has far surpassed the actual useful information available.

  In this talk, we'll cut through the noise and delve deep into the current applications, risks, and limitations of LLMs. We'll start with early research endeavours aimed at creating an "artificial brain" and trace the path that has led us to today's sophisticated text models. Along the way, we'll address how these models have been mistaken for intelligent systems.

  We'll shed light on the actual requirements for developing true artificial general intelligence, and see how far LLMs are from this goal. We'll end with a practical demonstration of how you can use LLMs in a way that plays to their strengths, by showing you how to build a system which leans into these models powerful natural language capabilities.

• Has Generative AI Already Peaked? - Computerphile (13 min. YouTube video).

  The paper mentioned in the video is this one: No "Zero-Shot" Without Exponential Data: Pretraining Concept Frequency Determines Multimodal Model Performance (PDF 47 MB).

• Jon Stewart On The False Promises of AI | The Daily Show (11 min. YouTube video).

• I've been employed in tech for years, but I've almost never worked by Dr. Emmanuel Maggiori.