#AI#AIHype#AIPin: "It emerged recently that Humane was trying to sell itself for as much as $1 billion after its confuddling, expensive and ultimately pretty useless AI Pin flopped. A New York Times report that dropped on Thursday shed a little more light on the company's sales figures and, like the wearable AI assistant itself, the details are not good.
By early April, around the time that many devastating reviews of the AI Pin were published, Humane is said to have received around 10,000 orders for the device. That's a far cry from the 100,000 it was hoping to ship this year, and about 9,000 more than I thought it might get. It's hard to think it picked up many more orders beyond those initial 10,000 after critics slaughtered the AI Pin."
According to this writer, we are currently witnessing the fifth hype cycle concerning AI:
#AI#GenerativeAI#AIHype#AIWinter: “History does not repeat itself, but it does rhyme. This hype cycle is unlike any that have come before in various ways. There is more money involved now. It’s much more commercial; I had to phrase things above in very general ways because many previous hype waves have been based on research funding, some really being exclusively a phenomenon at one department in DARPA, and not, like, the entire economy.
I cannot tell you when the current mania will end and this bubble will burst. If I could, you’d be reading this in my $100,000 per month subscribers-only trading strategy newsletter and not a public blog. What I can tell you is that computers cannot think, and that the problems of the current instantation of the nebulously defined field of “AI” will not all be solved within “5 to 20 years”.”
#AI#GenerativeAI#VCs#CashingOut#AIHype#SPVs: "VCs are clamoring to invest in hot AI companies, willing to pay exorbitant share prices for coveted spots on their cap tables. Even so, most aren’t able to get into such deals at all. Yet, small, unknown investors, including family offices and high-net-worth individuals, have found their own way to get shares of the hottest private startups like Anthropic, Groq, OpenAI, Perplexity, and Elon Musk’s X.ai (the makers of Grok).
They are using special purpose vehicles, or SPVs, where multiple parties pool their money to share an allocation of a single company. SPVs are generally formed by investors who have direct access to the shares of these startups and then turn around and sell a part of their allocation to external backers, often charging significant fees while retaining some profit share (known as carry).
While SPVs aren’t new – smaller investors have relied on them for years – there’s a growing trend of SPVs successfully getting shares from the biggest names in AI.
These investors are finding that the most popular AI companies, except OpenAI, are not all that hard for them to buy at their smaller levels of investing."
#AI#GenerativeAI#AIHype#GeoPolitics: "A popular view of generative AI is that it’s unjustifiably expensive, chronically wasteful, rarely useful, and is being foisted on the general public for ideological reasons even though it makes the services they rely on worse. Governments are sure to be all over it.
#AI#GenerativeAI#AIHype#Media#News#Journalism: "More broadly, across news media coverage of AI in general, reviewing 30 published studies, Saba Rebecca Brause and her coauthors find that, while there are of course exceptions, most research so far find not just a strong increase in the volume of reporting on AI, but also “largely positive evaluations and economic framing” of these technologies.
So, perhaps, as Timit Gebru, founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR), has written on X: “The same news orgs hype stuff up during ‘AI summers’ without even looking into their archives to see what they wrote decades ago?”
There are some really good reporters doing important work to help people understand AI—as well as plenty of sensationalist coverage focused on killer robots and wild claims about possible future existential risks.
But, more than anything, research on how news media cover AI overall suggests that Gebru is largely right – the coverage tends to be led by industry sources, and often take claims about what the technology can and can’t do, and might be able to do in the future, at face value in ways that contributes to the hype cycle."
#AI#GenerativeAI#AIHype#AGI: "The reality is that no matter how much OpenAI, Google, and the rest of the heavy hitters in Silicon Valley might want to continue the illusion that generative AI represents a transformative moment in the history of digital technology, the truth is that their fantasy is getting increasingly difficult to maintain. The valuations of AI companies are coming down from their highs and major cloud providers are tamping down the expectations of their clients for what AI tools will actually deliver. That’s in part because the chatbots are still making a ton of mistakes in the answers they give to users, including during Google’s I/O keynote. Companies also still haven’t figured out how they’re going to make money off all this expensive tech, even as the resource demands are escalating so much their climate commitments are getting thrown out the window."
"This whole AI cycle was fueled by fantasies, and when people stop falling for them the bubble starts to deflate. In The Guardian, John Naughton recently laid out the five stages of financial bubbles, noting AI is between stages three and four: euphoria and profit-taking."
I'm trying very hard to avoid getting sucked into the AI fad. It reminds me a lot of Crypto and Reactjs irrational exuberance.
Gonna wait til things calm down to resume my research.
It looks like my country will be forced to act as a giant battery for these global gibberish generators. Like it wasn't bad enough with crypto farms left and right.
"The study from Reuters Institute and Oxford University (via BBC), which surveyed over 12,000 people across six countries, seemingly reveals how little that AI hype has percolated down to real-world use, for now."
#AI#GenerativeAI#AIHype: "The reality is that A.I. models can often prepare a decent first draft. But I find that when I use A.I., I have to spend almost as much time correcting and revising its output as it would have taken me to do the work myself.
And consider for a moment the possibility that perhaps A.I. isn’t going to get that much better anytime soon. After all, the A.I. companies are running out of new data on which to train their models, and they are running out of energy to fuel their power-hungry A.I. machines. Meanwhile, authors and news organizations (including The New York Times) are contesting the legality of having their data ingested into the A.I. models without their consent, which could end up forcing quality data to be withdrawn from the models.
Given these constraints, it seems just as likely to me that generative A.I. could end up like the Roomba, the mediocre vacuum robot that does a passable job when you are home alone but not if you are expecting guests."