"No one should be surprised that artificial intelligence is following a well-worn and entirely predictable financial arc
[…]
For investment bubbles, the five stages are displacement, boom, euphoria, profit-taking and panic. So let’s see how this maps on to our experience so far with AI.
[…]
So, going back to that original question: are we caught in an AI bubble? Is the pope a Catholic?"
Not nearly enough.
The story of #Tesla reminds me of a #bubble, very much like the excellent article Cory @pluralistic wrote last December about two kinds of (tech) bubbles.*
Even though Tesla is just a company, its market cap and the weight of all of the #Musk brands taken together easily make up for lack of other competitors in this hypothesis.
The #TeslaBubble will be of the type that leaves something behind. A shaken up old car industry.
The most impressive accomplishment of the generative model bubble to date is in the sheer number of people who I used to respect but have disappointed me lately by chasing the bubble.
This is an irrational economic and cultural bubble. Participating in any way shape or form is already a no-win situation. You're too late to be one of the big winners and the bubble dynamic is already baked in and will only get less rational from now on.
The final part of my #PhD thesis has now been accepted and published in #Microplastics and #Nanoplastics! 🖖🥳📃🎓
I'm proud to have coauthored this study by Lisa Marie Oehlschlägel. We looked at water-air transfer of microplastics during #bubble bursting in lab experiments, with surprising results: https://doi.org/10.1186/s43591-023-00079-x 🌊🫧💥
Mr. Doctorow lays down the law: Of course #AI is a #bubble, the signs are all around. All bubbles pop eventually, we should be looking at what remains after: the little guys.
A thought provoking piece from @pluralistic — What Kind of Bubble is AI?
TL;DR: AI is a bubble filled with fraud and hype, and it's unclear what will be left when it bursts. Low-stakes applications may not generate much revenue, while high-stakes applications like self-driving cars and radiology require human oversight, making them more expensive. What happens when the exuberance ends and the server bills come due?
"Just take one step back and look at the hype through this lens. All the big, exciting uses for AI are either low-dollar (helping kids cheat on their homework, generating stock art for bottom-feeding publications) or high-stakes and fault-intolerant (self-driving cars, radiology, hiring, etc.)."
I’m more certain than ever that the first quarter of 2024 will see a grand reckoning for companies that have bet big on #AI. As I said before, I predict a lot of CFOs getting sticker shock at their compute bills, and we will see pivots and downscaling of expectations across the industry. By the middle of the year, there will likely be a general cool-down as users and investors come to grips with what “AI” can realistically do at reasonable cost (hint: not as much as the hype claims). Strategically deploying smaller models will become quite attractive, rather than monolithic solutions.
I also think 2024 is the year of the legal reckoning for the industry. Creators whose work have been used for training (i.e. plagiarized) will likely make big inroads into establishing legal frameworks for compensation, and some models will become poisoned because they were trained with unvetted data. Hopefully this also means that model-makers who have been meticulous about their training data’s providence will reap rewards.
@SheDrivesMobility@AufstandLastGen Was ist denn bitte unberechtigt, bzw. spaltend daran, wenn man darauf hinweist, dass sich eben jene Teile der Gesellschaft die #LetzteGeneration zu erreichen versucht, durch diese Formen eher auf Abwehrhaltung gehen? Ich bin mir der Dramatik der #klimakrise bewusst und habe auch Verständnis für die Aktionen der LG - bin aber eben nicht Zielgruppe. Die tickt eben anders als unsere #Bubble, respektive hat vordergründig andere Sorgen.
#AI#GenerativeAI#Hype#SiliconValley#Bubble: "Silicon Valley has seen wave after wave of hype cycle over the past decades — with mixed success. The infamous dot-com bubble saw companies go public and take hundreds of millions of dollars from retail investors simply for having a “.com” in their name. Countless social media companies battled for supremacy, but few remember names like FriendFeed and Yik Yak.
Meanwhile, billions of dollars have gone into building self-driving cars, but after years of development, the tech still isn’t ready for mass adoption, despite the predictions from tech luminaries that they would be widespread by the mid-2020s. Cryptocurrencies have seen their own cycles of excitement, most recently the bubble that peaked at the end of 2021, leading to millions of people losing money.
There was even a previous wave of AI venture capital hubbub in the mid-2010s, when scientific breakthroughs in image recognition, translation and other AI developments led to a burst of start-ups in the space. Many were acquired by Big Tech companies.
In the latest iteration, the tech behind chatbots such as ChatGPT and Google’s Bard are trained on huge amounts of data pulled from the open internet. That means big energy and computing needs. Nvidia, the company that makes the computer chips and software best suited to AI, has seen its valuation balloon over the last year, catapulting it into becoming the world’s sixth-most valuable company at $1.1 trillion."
Kabinettsklausur: Ampelkoalition hofft auf "Geist von Meseberg"
Dauerstreit, schlechte Umfragewerte und eine schwächelnde Wirtschaft: All dem will die Ampel bei der Kabinettsklausur in Meseberg etwas entgegensetzen. Kann das gelingen? Von M. Kubina.