AI: The Ups & Downs of New Tech. RTZ #310

...AI seeing the inevitable hype down-cycle

Following the adage of “What goes up, comes down”, the AI Tech Wave may be seeing its version underway at the end of the first quarter of 2024. The media in particular likes to focus on sentiment cycles, both on the way up and down. Especially if it involves AI industry leader OpenAI.

I’ve already discussed the recent reports of the relatively slower than expected ramp of AI products and services in the Enterprise. We’ve seen reports on the slower than expected ramp of OpenAI’s ChatGPT store, with its plethora of ‘GPTs’ on offer by third parties.

This week we see Axios’s report “Chatbot letdown as Hype hits rocky reality”. Complete with references to AI’s ‘mushy phase’. Here’s a taste, with a laundry list of links to the perceived down-cycles:

“Grumbles about generative AI's shortcomings are coalescing into a "trough of disillusionment" after a year and a half of hype about ChatGPT and other bots.”

“Why it matters: AI is still changing the world, but improving and integrating the technology is raising harder and more complex questions than first envisioned, and no chatbot has the magic answers.”

“Driving the news: The hurdles are everything from embarrassing errors — such as extra fingers or Black founding fathers in generated images — to significant concerns about intellectual property infringement, cost, environmental impact and other issues.”

• “Some leading startups of generative AI's first wave are falling by the wayside. Last week, Inflection AI's leadership and top researchers decamped for Microsoft, while on Friday, Stability AI's CEO and co-founder resigned as the firm faced a talent and financial crunch.”

  

The piece of course goes on to cite AI commentators who’ve been less enthusiastic on LLM AIs in general, bringing up the long-discussed issues of AI reliability, need for improved safety. With a focus of course on ultimate mainstream utility, traction, and adoption:

“What they're saying: Gary Marcus, a scientist who penned a blog post last year titled "What if generative AI turned out to be a dud?" tells Axios that, outside of a few areas such as coding, companies have found generative AI isn't the panacea they once imagined.

• "Almost everybody seemed to come back with a report like, 'This is super cool, but I can't actually get it to work reliably enough to roll out to our customers,'" Marcus says.”

“AI ethics expert Rumman Chowdhury tells Axios that the challenges are numerous and significant.”

• "No one wants to build a product on a model that makes things up," says Chowdhury, CEO and co-founder of AI consulting firm Humane Intelligence.”

• “And, even when such issues are addressed, Chowdhury says the technology remains a "party trick" unless and until work is done to mitigate bias and discrimination.”

  

Readers here know of course that I’ve also long talked about these downs and ups, with a long-term eye on the underlying secular technology ups that are driving the case for long-term optimism. And how the AI tech industry, like other tech waves before, tends to sell the tech ‘before it’s time’.

None of that of course changes with these near term of tales of AI ‘woes’. It’s part of the up and down sentiment shifts and cycles. But important to note, and keep in context. Stay tuned.

(NOTE: The discussions here are for information purposes only, and not meant as investment advice at any time. Thanks for joining us here)